0:18

Hello everyone , welcome back to another

0:20

episode of the Lunatics Radio

0:23

Hour podcast . I'm Abbey Brinker

0:25

sitting here with Alan Kudan . Hello

0:27

. And today we are talking about

0:29

the controversial subject

0:32

, the horror of artificial intelligence

0:34

. Is this controversial In some

0:36

ways ? I think AI is pretty controversial , for

0:39

sure . I think there's a lot of people , especially

0:41

artists , who are pretty

0:44

against . There's a lot of people , especially artists , who are pretty

0:46

against especially image generating AI .

0:48

Oh okay , so yes , the implementation of

0:50

AI in society is highly controversial

0:52

. Yes . But I think everyone

0:54

can agree that under the correct lens

0:57

, AI can be absolutely horrific

0:59

.

0:59

Oh yeah , I think that's hands down .

1:01

It's very scary .

1:02

Yeah , and this topic is really interesting

1:05

to examine through this lens right

1:07

of our podcast , which is the history of horror , because

1:15

, unlike most of our episodes , where there's this linear influence of

1:17

history onto a horror trope , artificial intelligence and AI

1:19

and pop culture advance like at

1:21

different rates . So , for instance

1:23

, in some cases AI

1:25

was represented in certain ways in

1:27

film and TV or books before

1:30

that existed in real life .

1:31

Oh sure , but that's technology in general

1:33

.

1:34

I know , but that's what I'm saying . Like usually we're like okay

1:36

, this is the history of clowns and

1:38

this is how clowns have been adapted for

1:40

horror , but in this case it's sort of

1:42

like sometimes it's something that happened in , sort of like , sometimes

1:44

it's something that happened in history , and sometimes

1:47

it's something that happened in a film and then history

1:49

caught up to it and it's just less of a

1:51

linear timeline when you're looking at the influence

1:53

of AI on pop culture .

1:55

I'm going to throw

1:57

one monkey wrench in there . Okay . And

2:00

say like , yeah , they weren't calling it artificial intelligence

2:02

. But there are stories of

2:04

humans building automatons for

2:07

millennia , you know . Think of the story of

2:09

like the golem , which that's just another

2:11

form of some kind of artificial intelligence made

2:14

by humans that goes rogue

2:16

and kills .

2:17

But that's sort of exactly what I'm saying In the

2:19

case of the golem right . I would categorize it

2:21

as like mythology , similar to

2:24

a film right . It's not real .

2:26

How dare you ?

2:27

That predates the invention

2:29

of an actual automaton

2:32

that does your bidding for you , or whatever

2:34

.

2:35

Sure .

2:35

There's films out there and books

2:37

and things that represented a thing

2:40

and now that thing exists , but when that book

2:42

was written it didn't yet I see

2:44

okay , yeah , it's like star trek

2:46

and the ipads .

2:47

Everyone says star trek predicted

2:49

the ipad , you know , because everyone just had

2:51

like little tablets and shit , right , and that

2:54

was the original star trek 60s . So

2:56

like , obviously that predates , you know , steve

2:58

jobs and his stuff right , but you

3:00

know all these things are . You know pop

3:02

culture influences technology . People

3:05

invented the ip iPad because that's what they

3:07

thought the future should look like .

3:09

Right , exactly that's and that's a really fun

3:11

new sort of twist for this episode , like

3:13

, in some ways , I feel like instead

3:16

of history influencing horror , in

3:18

this case horror has influenced

3:20

history . It's a fun . It's a fun remix

3:22

episode , if you will , isn't it also like the simpsons

3:25

has predicted a bunch of stuff that's come to be

3:27

?

3:27

uh , yeah , I mean I have

3:30

not watched too much of the simpsons , but I know that's

3:32

a , that's a meme yeah , you know I

3:34

just looked up the the definition , just because

3:36

this seems applicable to this episode . And

3:39

a meme is an element of a culture

3:41

or system of behavior passed

3:43

from one individual to another by

3:45

imitation or other non-genetic

3:47

means .

3:48

Interesting .

3:49

It's like a collective

3:52

consciousness that is passed

3:54

actively . So if something is popular

3:56

, it gets passed on , If it is not popular

3:59

, it does not get passed on , which is very

4:01

similar to

4:03

evolution Darwinism , right yeah , but in

4:05

this case it's all about information

4:07

.

4:07

Fascinating .

4:08

More on that later .

4:10

Yes , okay . So before we get into it , let's cite

4:13

our sources . We have a Harvard

4:15

article by Rockwell Anoya

4:17

the History of Artificial Intelligence

4:20

. A Forbes article A

4:22

Very Short History of Artificial Intelligence

4:24

by Gil Press . An article

4:26

by Christina Sayez Machines

4:28

Now Know how to Terrorize Humans

4:31

from CCBcom , which is part

4:33

of MIT . A VentureBeatcom

4:35

article what the Evolution of AI's

4:37

On-Screen Depiction Says About Society

4:40

. A Variety article by Zach Scharf

4:42

. Arnold Schwarzenegger proclaims the

4:45

Terminator has become a reality due

4:47

to AI . It's not fantasy

4:49

or kind of futuristic anymore . A

4:51

Wired article by Maria Streszynski

4:54

how Christopher Nolan learned to stop

4:56

worrying and love AI . A Guardian

4:58

article how soon will Megan become

5:00

reality ? Robot ethicists weigh

5:03

in Film Days . Article by Leanna

5:05

Hindley Artificial Intelligence in

5:07

Isolation in Duncan Jones's Moon

5:09

10 Years Later . An Air and Space

5:11

article by Paul Caruzzi 2001

5:14

A Space Odyssey , hal and the Future

5:16

of AI . And of course these will be

5:18

in the description of the episode as well

5:20

.

5:21

Also lots of movies and

5:24

at least one video game .

5:25

Lots of movies . So first

5:28

let's define artificial

5:30

intelligence not to be that person but

5:32

Webster's Dictionary defines

5:34

Actually . Use the Oxford English Dictionary

5:37

.

5:37

You would .

5:38

AI is both the theory and development

5:40

of computer systems that are

5:42

able to perform tasks that normally

5:45

require human intelligence , such

5:47

as visual perception , speech recognition

5:49

, decision making and the translation

5:52

between languages . And to add

5:54

on , I think a big part of this is the ability

5:56

of AI to learn from inputs and

5:58

evolve on its own . So I'm going to start us off

6:00

with a quote from the Harvard article by

6:02

Rockwell Anoya Quote . I'm going to start

6:05

us off with a quote from the Harvard article by Rockwell

6:07

Anoya Quote . In

6:10

the first half of the 20th century , science fiction familiarized the world with

6:12

the concept of artificially intelligent robots . It began with the heartless Tin man from the

6:14

Wizard of Oz and continued with the humanoid

6:16

robot that impersonated Maria in

6:18

Metropolis . By the 1950s

6:20

, we had a generation of scientists , mathematicians

6:23

and philosophers with the concept

6:25

of artificial intelligence , or AI

6:28

, culturally assimilated in their

6:30

minds .

6:30

Hang on . When the heck did the Wizard of Oz come out

6:33

?

6:33

1939 .

6:34

Okay , and when did Metropolis come out ?

6:36

1927 .

6:38

Oh , but it was a book first . I just can't

6:40

picture Metropolis coming out after the Wizard

6:42

of Oz . But the Wizard of Oz movie

6:45

came out later . It was just

6:47

the book was before , all

6:49

that .

6:50

Yes , yes , okay , back to the quote . One such

6:52

person was Alan Turing , a

6:54

young British polymath who explored

6:56

the mathematical possibility of artificial

6:58

intelligence . Turing suggested that humans

7:01

use available information , as well

7:03

as reason , in order to solve problems

7:05

and make decisions . So why can't machines

7:08

do the same thing ? This was the logical

7:10

framework of his 1950 paper

7:12

Computing Machinery and Intelligence

7:15

, in which he discussed how to build intelligent

7:17

machines and how to test their intelligence

7:19

. End quote .

7:20

I'm only familiar with the Turing test .

7:23

I want to say this the inception

7:25

of AI is super complicated

7:27

and kind of boring and we're not going to spend a ton of time

7:29

on it . But just to kind of clarify the quote

7:31

that we just read Alan Turing is

7:33

responsible for like conceptualizing

7:36

in a lot of ways in the modern sense of AI

7:38

, what that could look like . It

7:40

wasn't actually implemented until

7:42

a little bit later , and we'll talk about that . He's

7:44

kind of the seed , if you will

7:46

, but he's not the one who actually brings it into

7:48

3D .

7:49

Do we talk about the Turing test now or later ?

7:51

We can talk about the Turing test now , because

7:54

it will also come up

7:56

in a lot of the films .

7:58

My understanding of it is it's

8:00

simply a test on humans

8:02

. They interact with a machine

8:04

or they don't , but the test is

8:06

for the human to try to identify if

8:09

they think that what they're engaging

8:11

with is human or a machine , and

8:13

if a machine passes the

8:15

Turing test , it fooled the

8:17

user into thinking it

8:19

was a human .

8:20

Right , and films like Ex Machina

8:22

obviously play into that in a big way .

8:24

I mean yeah , they literally talk about the Turing

8:27

test .

8:27

But just the general . Honestly , let's pause here , because

8:30

just the general idea that

8:32

robots could fool humans , especially

8:34

AI , is like central

8:36

to everything we're going to talk about today , Like all

8:38

of the fears of humanity around

8:40

AI . In horror films it's

8:43

less so like oh , they're going to steal our work

8:45

as artists . Really , in horror , for

8:47

the most part , it's more like , oh

8:49

, the machines and the robots are going to trick

8:51

us and overrule us and become

8:54

the higher power in society

8:56

. So I think it's really interesting that even Alan

8:59

Turing back in the 1950s , like one of

9:01

the initial people to think

9:03

about this , is famous for

9:05

creating this test . Right , it kind of tells you that

9:07

there's always been this fear a little bit .

9:09

I'd say that there are two

9:11

branching tree Actually , it's not even

9:13

a branch , it's more of just a scale

9:15

how the whole like robots

9:18

impersonating humans is like

9:20

the first step of infiltration

9:24

and overthrowing and everything . But that's

9:26

not the end game . The end game is

9:28

when they just completely shed any

9:30

similarities to humanity , because

9:32

they don't need to fool anymore . They've already

9:34

won , just like . Imagine that

9:37

the human body could be rearranged right

9:39

. We build tools to

9:42

do certain tasks . Imagine

9:44

if your hand was instead

9:46

a hammer , or your arm was a chainsaw

9:48

, or your legs were wheels

9:50

if you wanted to go fast , right . Instead

9:53

of pretending to be humans

9:55

, they would basically build themselves to

9:57

emulate whatever task needed doing .

9:59

Are you talking about Transformers here ? I

10:01

feel like it depends on the universe . No

10:04

, Transformers is still in the

10:06

uh infiltration stage

10:08

right , but I think it depends on

10:10

are you talking about , like in film and tv or in

10:12

real life , that that's what machines will

10:14

?

10:15

that's like the end game so I

10:17

mean , I guess it's both right , because film

10:19

and tv is just predicting what's going to happen

10:22

, you know whatever . Okay

10:24

, a great example is

10:26

Terminator . Okay . So in

10:29

present day , or the past or whatever

10:31

you want to call it in in the first one

10:33

, in 1984 , the Terminator

10:35

is sent

10:38

from the future to 1984 to

10:40

kill the mother of the leader of the resistance

10:42

. Right , that's the premise of terminator . Yep

10:44

, he looks like arnold schwarzenegger

10:47

, but that is because he is an infiltration

10:50

assassination bot . He's supposed

10:52

to look like a human so he can navigate

10:54

through society unhindered

10:57

, uh , and not just have , like all society

10:59

, like fight him and kill him , right . However

11:01

, when you go to the future of

11:03

the far distant 2029

11:05

, there's no like flesh

11:08

covered robots . They're all you

11:10

know , either these walking , you

11:12

know skeletons , or they

11:14

are these giant hulking machines , you

11:16

know quadrupeds with giant

11:18

machine guns strapped to them , giant

11:20

flying jet things with arms

11:23

because they just don't need to

11:25

hide .

11:25

I mean , yeah , that makes sense . If there's no more humans

11:28

, or if you've dominated humanity

11:30

, then there's no need to trick .

11:32

In preparation for this , I started rereading

11:34

Robopocalypse Great book Very

11:36

topical and in

11:38

that they made a really good point how

11:41

, when machines start

11:43

building themselves , they

11:48

never build something that looks like a human , because a human

11:50

is just inefficient for most

11:52

tasks . It's very versatile

11:54

, can do lots of things , but

11:57

like look at the animal kingdom , you

11:59

know if you want to be fast , you go on

12:01

four legs , you want to be

12:03

able to swing around

12:06

. Then you need like super long arms like

12:08

a monkey . Humans can swim , but

12:10

like fish are a lot better . All these things

12:12

are we're versatile , but

12:14

they're not optimized and so , especially

12:16

once you get into trying to build a

12:18

giant death machine , a

12:20

bipedal machine

12:22

is very inefficient compared

12:24

to something that can run on four legs

12:26

is it has its own outriggers

12:28

for shooting a giant gun . You know there's

12:31

there's lots of these little nuances

12:33

that a machine would care about

12:35

simply on the efficiency scale , but

12:37

because they're not worried about aesthetics

12:40

but the real question is is the

12:42

machine're talking ?

12:44

okay , so you're talking about machines

12:46

that are aware that they're boy

12:48

and you kill him or you whatever

12:50

like . What's the ethics of that ?

12:51

Yeah , Just

13:13

imagine you know there you are

13:15

murdering and

13:17

you shoot somebody and a bunch of circuits fly out .

13:20

I mean more so , like you purposefully .

13:21

You're like oh , thank God .

13:23

Okay , let's get back to the outline here . So

13:25

artificial intelligence officially came

13:27

into existence in the 1950s . In

13:30

1951 , a calculator

13:32

nicknamed SNARK was known

13:34

. S-n-a-r-k stands

13:36

for Stochastic Neutral

13:38

Analog Reinforcement Calculator

13:40

.

13:41

Okay , so what does stochastic mean ?

13:43

Technical statistics . We

13:45

looked it up . Something like that , something

13:47

beyond my comprehension .

13:49

I believe it is able to

13:51

pull from a random probability , but

13:54

being able to statistically evaluate

13:57

that probability without having a

13:59

guaranteed outcome .

14:01

So SNARK was invented by Marvin Minsky

14:03

and Dean Edmonds

14:06

. It was the first artificial

14:08

neural network and used about

14:10

3,000 vacuum tubes to

14:12

simulate neurons . That's so

14:14

many . One year later , in 1952

14:17

, the first computer program

14:19

able to learn on its own was created

14:21

by Arthur Samuel . It was a checkers

14:24

game . In 1955 , the phrase

14:26

artificial intelligence was coined within a proposal

14:28

for a workshop which took place one

14:30

year later in 1956 . The

14:33

proposal came from Claude Shannon of

14:35

Bell Telephone Labs , marvin Minsky

14:37

, again of Harvard , john McCarthy

14:39

of Dartmouth and Nathaniel Rochester

14:41

of IBM . The workshop is largely

14:44

considered to be the official birth of AI

14:46

as we think about it today . Also in 1955

14:49

, the logic theorist was developed

14:51

. Quoting from the Forbes article by

14:53

Gill Press quote in December

14:55

1955 , herbert Simon

14:58

and Alan Newell developed the logic

15:00

theorist , the first artificial

15:02

intelligence program , which eventually would

15:04

prove 38 of the first 52

15:06

theorems in Whitehead and Russell's

15:08

Principa Mathematica end quote

15:11

. Throughout the next few decades there continued

15:13

to be advancements in AI technology

15:15

in a huge way and I'm not going to go

15:17

through sort of the timeline of

15:19

AI , but we know right kind of generally

15:22

where we are today . It's been a big

15:24

year . Last year there was ChatGBT , there is AI kind of exploding all over the place right , kind of generally where we are today . It's been a big year Last

15:26

year , chat GBT . There is AI kind of exploding

15:28

all over the place right In visual aspects

15:31

, in chatbots , in

15:33

AI being able to like , generate

15:36

video and artwork

15:38

for people and text

15:40

and images and stories and songs , and

15:43

that's where sort of the great debate comes into play

15:45

. But all of that being said , that's

15:47

kind of the rundown of how it initially started

15:49

.

15:50

So I spent a month of last

15:52

year working for

15:54

a company that

15:56

had me sign an NDA . This

15:58

entire campaign was

16:00

all about making all these videos

16:02

about why AI is not

16:05

scary and why it's actually

16:07

a good thing , and we actually outlined

16:09

some of the really really incredible applications

16:12

that AI is doing right now that

16:15

you just don't hear about .

16:16

Tell us , tell us the silver lining .

16:17

I can't because of the NDA .

16:19

Okay , well , I'll just say this based on my

16:21

research , not on your job , that

16:24

I think there's like anything

16:26

in the world . There are many , many

16:29

sides to this and obviously

16:31

I think , when it comes to the

16:33

protection of creative works and

16:36

the reuse and the training against

16:38

those things , there are huge concerns there , there

16:40

needs to be regulation and there needs to be systems

16:42

figured out . On the other hand

16:44

, I think that there's a lot of . There's

16:47

something like , for example , we have huge

16:50

years for tornadoes , right , and the tornado

16:52

belt . What if AI

16:54

was able to predict when tornadoes

16:57

were going to hit by reading weather patterns before

16:59

we could , and was able to automate

17:01

an alert to those places before

17:04

quicker than a human could even do the calculation

17:06

? It's some it's things like that

17:08

that I think could

17:11

be hugely beneficial , and , of course , there's always

17:13

pros and cons to all of these things . But , in

17:16

, there should be regulation and there should be all of these things , but

17:18

do I think it could also ultimately

17:20

help save lives ?

17:22

Yes , yes , absolutely . That's

17:24

a fantastic implementation of AI

17:26

. Anytime you have an

17:28

insanely large data set

17:31

that , through analysis

17:33

, can save lives , yeah , that's great . It's

17:35

when things get

17:37

pushed one step further

17:40

that people start to get nervous . Well

17:42

, there's two . One is A

17:44

. It's taking jobs .

17:46

Taking jobs and plagiarizing right

17:48

.

17:49

That's another . Plagiarism is a whole other story

17:51

. Yeah , there are people out there that

17:54

their entire job is to analyze

17:56

weather patterns and predict tornadoes . Guaranteed

17:59

Someone's job is that . Yeah , if AI can

18:01

do that with massive efficiency

18:03

. I'm sorry for Mr Tornado

18:05

Watcher or Mrs Tornado Watcher , but

18:08

like , yeah , your job might be

18:10

on the chopping block .

18:10

Well , I think that's a different example , because

18:12

I think if you are someone who is a

18:14

specialized scientist in Tornado

18:17

Watch , there needs to be human checkpoints

18:19

with these things , right , and so there's probably only

18:21

so many people in the world to do that . But

18:24

if you're if we're talking about like toll booths or

18:26

something simple , I guess it could take millions

18:28

of jobs , right For something that's less specialized

18:31

, for sure .

18:32

Right , and that happened a while ago . You

18:34

know , toll booths got automated , yeah

18:36

, a while . You know . Now there's cameras that snap

18:38

your license plate and then just mail you shit , exactly

18:41

. But in getting back to the tornado

18:43

example , yes , there

18:45

are very trained people and

18:47

these algorithms are going to

18:49

need to be trained by these trained people

18:52

to make them correct in the first place . So

18:54

you know , I'd say for a couple of generations

18:57

, your job is , that job is safe

18:59

. I don't think it's a great time to start going into

19:01

the field of training , because the AI is going to outpace anybody , but for those already in it , you're

19:03

going to start going into the field of training , because the ai is going to outpace

19:05

anybody . But for those already in it

19:07

, you're going to be okay , you just have

19:09

to ride that wave . But the

19:11

next step after this is like and here's

19:13

when , like , the science fiction starts kicking in what

19:16

if ai could take the next

19:18

step and stop tornadoes as

19:20

seen during the the beijing olympics

19:22

? Like china has the ability

19:25

to curb weather patterns

19:27

with missile launches , they literally

19:29

blew storm clouds away so that the opening

19:31

ceremonies would be fine .

19:32

Did you hear what happened this week ?

19:34

No , what happened this week ?

19:35

So now this will be probably a week delayed

19:37

for those listening , but a group of scientists

19:40

on Tuesday launched

19:42

. It looks like a cannon

19:45

but they went out on a boat in california like a deprecated

19:48

aircraft carrier deprecated

19:50

like it's not in use as an aircraft carrier

19:52

. They launched from this

19:54

cannon sea salt into

19:57

the atmosphere to reflect

19:59

light back , to make the clouds

20:01

brighter , essentially , and reflect the light from the sun

20:03

back into space to cool the clouds brighter , essentially , and reflect the light from the

20:05

sun back into space to cool the earth

20:07

. And they are . We're so afraid of the pushback

20:10

. Because it's actually interesting . I was just reading like the

20:12

New York Times article about it . But even reading

20:14

it you get the sense of like holy shit , like

20:16

I am all for whatever we need to do to

20:18

save the earth , but there's this like sense

20:21

of unnaturalness or like this

20:23

God complex of like wow , we're about to

20:25

change the climate , like

20:27

we are about to fuck with weather

20:30

.

20:30

Well , we already did . Now they're trying to change

20:32

it back .

20:33

No , I know , but like in this , like really like concrete

20:35

, clear way , I don't know there's something about it where you're like whoa

20:38

, but they're so afraid of the pushback

20:40

they

20:45

did it in secret and it went well and they're gonna do a bigger test now , or

20:47

it'll be a higher , you know , explosion or whatever but what movie

20:49

was it ?

20:50

it wasn't the matrix , I don't think

20:52

, but it's another science

20:55

fiction film that effectively nukes

20:57

the sky to try to curb climate

20:59

change . It adds a permanent

21:02

cloud barrier right . But like dark

21:04

clouds , and then things go too far , it gets

21:07

out of control .

21:08

And that's the fear . Right Like what if they do

21:10

this ? But it has some effects

21:12

. They're not thinking of what if suddenly ?

21:14

Ice age .

21:15

Right , truly Like what if it just goes too

21:17

far , you know ? And so it's exciting

21:19

, but it's also scary , right ?

21:21

This is the only planet we've got . We

21:24

don't have the luxury of like well , we fucked this

21:26

up . Guess we can't play on this here . Fun

21:28

playground in Ukraine anymore .

21:30

There's a callback to our amusement parks . Episode

21:32

.

21:33

But steps need to be taken , but

21:36

very carefully calculated

21:38

steps .

21:38

Yeah , it just feels like I don't know with all of

21:40

this stuff , like it just feels like and

21:47

they say , millennials always feel like this , so maybe I'm just a silly

21:49

basic millennial but it feels like we're on the precipice

21:51

of like some real changes , like some total shift in everything

21:54

about the world . You know , we're fucking around

21:56

with AI , with weather

21:58

patterns , with whatever other secret

22:00

things are happening that we don't know about Aliens

22:03

. The government is like yes , there are . Like

22:08

it just feels like everything is like kind of culminating and coming together . And I don't want to be

22:10

an alarmist , you have russia kind of going off as they . You would love to be an alarmist

22:12

what , like how is it all gonna play

22:14

out ? You know just feels like there's a lot , a

22:16

lot going on .

22:17

That's it's because there is , and I know there

22:19

always is , but I don't know every generation

22:22

feels like theirs is the most important

22:24

generation to have ever lived , and maybe

22:26

they are .

22:27

But I sort of feel like is this it ? Like

22:29

is some crazy shit's going to happen , you

22:31

know , or they're going to shoot the salt into the cloud

22:33

and then AI is going to trigger

22:36

and like suddenly it's going to be a nuclear winter

22:38

. You know , I don't know . It just feels like lots

22:40

of gambling going on .

22:42

I wish I knew what movie that was . It was just

22:44

so . I don't think it's the

22:46

Matrix , but like the same thing happens , but

22:48

not for climate change reasons . In the Matrix

22:50

they nuke the sky with

22:53

the permanent Operation Dark Skies , I

22:55

think because the primary fuel

22:57

source for the machines is

22:59

solar . So they figure if they just block

23:01

out the sky temporarily they

23:03

would lose their fuel source and then they'd

23:06

win . But instead they did it permanently

23:08

because they're awesome , and then humans

23:10

just got enslaved and turned into batteries , so

23:13

it kind of backfired there .

23:14

There you go . Ok , so I

23:16

sort of tease this at the beginning , but again , for

23:18

me the history of AI in

23:20

pop culture and horror seems

23:22

somehow more interesting than

23:25

the history of AI in reality , until like

23:27

this year , right , like all of my favorite

23:29

topics , this story touches on

23:31

Mary Shelley's Frankenstein .

23:34

It does .

23:35

Now here's two things . One is that

23:37

there is an argument out there

23:39

for sure that Frankenstein as a story

23:41

explores AI , and

23:44

that's an argument . It depends on how you think of

23:46

consciousness and reanimation and

23:48

technology and all these things . I'm not here to talk

23:50

about that today , unless you want to .

23:53

No .

23:53

What I'm here to talk about is

23:55

back in October 2007

23:58

, an AI program named

24:00

for Mary Shelley , called Shelley , was launched

24:03

. It read horror stories

24:05

from Reddit's famous NoSleep subreddit

24:07

, which is one of my favorite places

24:09

on the internet , and it learned how to

24:11

write horror stories of its own . Yeah

24:14

, and so this isn't like I don't

24:16

know , a huge moment in AI history , but

24:18

I think it's no longer . I don't

24:20

think it exists anymore , but it's interesting

24:22

because this was back in 2017 and

24:24

it was doing something that , in a lot of ways , chat

24:27

, gbt and other programs are doing now

24:29

, also because we're horror . We love

24:31

horror , you know . I think it's interesting . There's certainly

24:34

a debate , and actually one of our friends

24:36

reached out and they were like you're going to for for

24:38

the horror stories for AI , you're , you're

24:40

going to have AI generate a story , right

24:42

, but no , we're not , because you know

24:44

, for us , the stories that are

24:46

submitted are , you know , are written with so

24:48

much love and talent and we

24:50

want to preserve that for sure on the show

24:52

. But I think it's kind of an interesting debate

24:54

, you know .

24:55

Yeah , AI stories are fine

24:57

, but that's all . They are Just fine , Nothing

24:59

special . I'm sure that there's a collection of best

25:02

AI stories of all time , but I have yet

25:04

to see one that's like man . This

25:06

is great .

25:07

Do you spend a lot of time reading AI stories

25:09

?

25:10

I've browsed , there's like a massive

25:12

collection of this crap on Amazon because

25:14

it's so easy to self-publish , right

25:17

, and so people just have AI generate

25:19

a book , right , and then they generate

25:21

a cover image that

25:23

is provocative and they sell it on amazon .

25:24

Provocative and they sell it on amazon .

25:26

Yeah , if they sell one

25:28

copy , they've made a profit yeah

25:30

because this costs them nothing except a little bit of

25:32

time super .

25:33

True , the first film to play

25:35

with the idea of artificial intelligence

25:37

is often thought to be metropolis , dating

25:40

back all the way to 1927

25:42

and a film that I had a

25:44

deep love for back

25:46

in my college years . Really

25:48

. I had a big Metropolis poster over my dorm

25:50

room bed .

25:51

Wow why .

25:52

I loved it . I thought I just like the aesthetic of the

25:54

film , more so , honestly , than the

25:56

content . But the aesthetic of the film

25:59

was so fascinating to me and like this , these like little micro special

26:01

effects and things they did with miniature . You know , it just was like fascinating to me . And like this

26:03

, these like little micro special effects and things they did with

26:05

miniature . You know , it just was like

26:07

fascinating to me .

26:09

The effects hold up , they're still great .

26:11

Yeah , I love , I love it . Anyway , metropolis

26:13

is a German expressionist film by

26:15

Fritz Lang that was inspired by a 1925

26:18

novel . In the film , a robot

26:20

is created based on the likeness of a woman

26:23

named Maria . While the film is making

26:25

a point about labor , a lot of the film is

26:27

really about labor , scientific

26:29

advancements and the divide between the working

26:31

class and the affluent all points

26:34

that are still valid today . The big takeaway

26:36

for this episode is that this robot

26:38

modeled after Maria , called Machine

26:40

and Mench , is able to totally uproot

26:43

the labor system in metropolis and work

26:45

tirelessly day and night . So exactly what

26:47

alan and I were just talking about . Right ? Obviously

26:49

we all have fears that ai could take our jobs

26:52

, and this film tells that story . Quoting

26:54

from the venture beat article . Quote the

26:57

machine and mensch was a proto-artificial

26:59

intelligence and , like ai

27:01

, characters that come after she reflected

27:03

her time . Over the past century , ai

27:06

on screen has represented our anxieties

27:08

, hopes and ambitions , as

27:10

well as our deepest values . Of course

27:12

, that focus has shifted over time . Today

27:15

, when our real-life artificial intelligence

27:17

has become adaptable and dynamic , human

27:19

mimicking , ai seems less a fantasy

27:22

and more a not-too-distant

27:24

eventuality . Because

27:27

of this , our perceptions and expectations of AI on screen have shifted

27:29

and we have begun a new exploration

27:31

of what it means to be human . The future

27:34

of AI is threatening , exhilarating

27:36

, enwrapped in uncertainty and opportunity

27:38

, as it has always been . But as

27:40

AI has developed , so has our expectations

27:43

of it . End quote . A major

27:45

moment for artificial intelligence and

27:47

horror came with the first Stepford

27:49

Wives film from 1975

27:51

.

27:52

Wait , it was from the 70s , it's from the 50s

27:54

.

27:55

No , it's based on a novel from 1972

27:57

. Interestingly , the novel

27:59

is by Ira Levin , who is also

28:01

known for writing Rosemary's Baby , the novel

28:03

that predated the film . The first

28:06

film adaptation of the Stepford Wives

28:08

was directed by Brian Forbes and

28:10

, similar to the novel , it tells the story of

28:12

a young mother , wife and photographer who

28:14

moves her family , including a husband

28:17

and two young kids , out of New York City to the

28:19

suburbs of Connecticut . Our protagonist

28:21

, joanna , soon realizes that there's

28:23

something very bizarre about her new town

28:25

. Not only are all of the women stunning

28:28

and able to keep their homes perfectly clean

28:30

, they seem to lack emotional and

28:32

intellectual substance . They also

28:34

seem , to be like , obsessed with having sex with

28:36

their husbands , which is obviously not

28:38

super standard . This is because the

28:40

women in Stepford are replaced by robot

28:43

versions of themselves . Largely

28:45

, the Stepford Wives is a feminist work , using

28:48

robots to draw an obvious metaphor to women

28:50

and their perceived roles in society and

28:52

at home . During this time period , I

28:54

watched the original and I also watched the Nicole

28:57

Kidman remake , which is not

28:59

amazing , but it's kind of interesting . I feel

29:01

like they try to do something a little

29:03

bit different with it . They try to make it a little

29:05

quirky . Okay , and it

29:08

has , you know , like a different twist at the end . But

29:10

it's really interesting because there are

29:12

a few films that we're going to talk about today that

29:14

also explore the intersection

29:16

of like sexuality and AI . And

29:19

I think Stepford Wives and you know , in a

29:21

very like vague way , not

29:23

an explicit way is one of those . Sure

29:25

, obviously ex machina is one

29:27

, ai artificial intelligence is another

29:29

the film , but it's interesting

29:32

that it is somewhat of a consistent

29:34

theme because sex

29:36

is such a big part of being a human . It , you

29:38

know it makes sense . What I also really

29:40

love about the Stepford wives and the interpretation

29:43

of AI is that , again , it's looking

29:45

through this feminist lens which makes

29:47

it like a standout from a lot of the

29:49

other science fiction . Like

29:51

you don't often get a lot of like science fiction

29:53

feminism , unless it's like the Handmaid's Tale

29:55

or something that's very dystopian , and

29:57

instead Stepford is like this tiny

29:59

community that is rooted

30:01

in the normal world . It's not saying

30:04

like this could happen , we're going down

30:06

this wrong path . It's kind of making the point

30:08

of like this is where we are now . Sure

30:10

. The other interesting thing . So Ira

30:12

Levin , who wrote the original

30:14

novel Stepford Wives , wrote

30:16

Rosemary's Baby , which is also again

30:18

a very feminist . I think look at a

30:20

horror story , but just kind of

30:23

fascinating . It's not again often

30:25

that you have a man writing these feminist horror

30:27

works . That's kind of cool .

30:28

It's very rare for a man to write a woman well

30:30

.

30:31

That's what you've always said .

30:31

Because it's true , every

30:34

so often you get them and you're like huh weird

30:37

. Look at you and your

30:39

three-dimensional hopes and dreams .

30:41

The themes of Stepford Wives and the

30:43

treatment of AI have some similarities

30:45

to the film Artificial Intelligence from 2001

30:48

. Artificial Intelligence from 2001

30:50

may have had a big impact on you

30:52

.

30:53

Sure did .

30:53

It certainly did on me . I feel like every

30:55

one of our friends who I've talked to about this have been like holy

30:57

shit , yeah , that movie , Did you see

30:59

it when it first came out ?

31:01

Yeah , because this was coming off prime

31:03

Spielberg years . This is a Spielberg

31:06

movie . Have the kid from the

31:08

Sixth Sense , yeah . And you're like hot

31:10

dang , this is going to be crazy

31:12

. And then you watch it

31:14

and it's so sad

31:16

, it's sad , it's just

31:18

sad the entire time .

31:20

It's very sad . It's hard to watch . I

31:22

mean , it's not a bad film , but it's just

31:24

. It's so fucking weird it is . So

31:28

let's talk a little bit about it . Like you said , it was

31:30

directed by Steven Spielberg . It stars

31:32

Haley Joel Osment , jude Law and

31:34

William Hurt and here's a fun fact , alan

31:36

. The

31:44

film is loosely based on a short story from the 60s and in the 70s . Stanley Kubrick actually

31:46

acquired the rights but never ended up making the movie because he thought that the

31:48

computer graphics available at the time

31:50

weren't good enough to yet tell the story

31:52

.

31:53

That was a great call , Stanley .

31:55

So Spielberg actually dedicates the film to

31:57

Kubrick when you watch it .

31:59

That was nice of him . Probably a legal thing yeah

32:01

.

32:01

I don't know . I think he , you know , you

32:04

learn about like how in you know these big

32:06

directors , like they , they have visions

32:08

and they acquire the rights to things and they hold

32:10

them for decades and decades and you know

32:12

. And so Spielberg eventually made the

32:14

movie when the effects caught up

32:16

and I think the effects sort of still stand

32:18

to this day . I think they did a good job with that .

32:21

Speaking of holding on to movie rights and doing

32:23

absolutely nothing with them . Freaking

32:26

Leonardo DiCaprio he's got like

32:28

a bunch . He

32:35

just keeps snapping up these movie rights to like cool , cool things . But

32:37

I'll never forgive him because he has the movie rights to akira . What's that ?

32:39

one of the best anime movies ever

32:41

made do you think he wants to be a director

32:44

in his second era ? Definitely . Has he directed

32:46

anything yet ?

32:46

who cares um ? But it's

32:49

like that's what they all want . They want

32:51

to be stars and then move

32:54

into directing because they think they can do it better . I

32:56

think he wants to be clint eastwood I mean it's not

32:58

a bad .

32:58

Uh , I think he could probably .

33:00

No , it's , he has the clout to do it once

33:02

you start aging out of roles

33:04

, then you just

33:07

start making movies that

33:09

put your very recognizable

33:11

name and face in

33:13

more appropriate roles .

33:15

Do you think it's that or do you think it's

33:17

that you get so like

33:19

? This is my theory . It could be wrong , but

33:22

when you are someone who is a Leonardo

33:24

DiCaprio , you are so

33:26

famous you have sort of hit

33:28

the peak of fame that you

33:31

can hit in your current path

33:33

. Right , of course you can win more Oscars and whatever else

33:35

, but do you feel like it's like this ? It's

33:37

like CEOs . It's like you're a certain

33:39

type of person that landed you in this place and

33:42

you're just always going to be hungry for more . So

33:44

, ok , you've conquered acting . Now you're like I

33:46

want to conquer directing .

33:47

That's exactly it . You know , you're that CEO

33:50

that does great in I

33:52

don't know something

33:57

boring , and then you're just like fuck it , I'm going to leave this and go all in on crypto . Yeah

33:59

, you know , it's just because it's new and exciting and you have that golden parachute

34:01

to do whatever you want .

34:02

And I think you just have to be a certain type of person

34:04

to be a CEO . You know , you

34:06

have to be a little bit , there has to be some ego

34:09

and there has to be some certain things that all fall

34:11

into place for you to like really be

34:13

in that position .

34:15

That's actually been disproved

34:18

, simply because one

34:20

of the conversations about the absolute

34:22

best applications for

34:25

AI is replacing CEOs

34:27

.

34:27

But that doesn't mean that the people who are CEOs

34:29

don't share common traits , but that doesn't mean that the people

34:31

who are CEOs don't share common traits .

34:33

Correct , it takes a certain type of person to

34:35

win the position , yeah , but to do

34:37

the position .

34:38

No , of course .

34:39

Is actually a very . You

34:41

just got to follow very certain

34:43

rules . Yeah . In

34:53

this situation do this thing In this situation , do this thing , you know whatever makes the

34:55

most logical sense to progress the company . They're one . Once it's just too much power and that's

34:57

why , like , they run all these models where they just

34:59

make an artificial ceo

35:02

that just gives

35:04

the company guidance yeah

35:06

based off the insane amount

35:08

of information coming in . When you

35:10

run some kind of like global multi-billion

35:13

dollar company , there's just a lot

35:15

of data to consider and as soon as that

35:17

is the bottleneck , you

35:19

need something more than one

35:21

guy with an Oedipus complex yeah

35:23

, yeah , well , that's why you have a board . But yes

35:26

, totally right you have a board , uh

35:28

, to hopefully delegate , but

35:30

it all still comes down to like no , a board

35:33

is an advisory board .

35:34

They don't work for the company . Their whole job

35:36

is to make sure the strategy of the company is

35:38

right . Really , their whole job is to check

35:40

the CEO .

35:42

That's the executive board .

35:43

No , that's the advisory board .

35:45

Advisory board . So that's not like the COO

35:47

.

35:48

Right , that's like your C-suite .

35:49

That's like your executive leadership team .

35:51

A board sits outside of the company . They're

35:54

employed by the company .

35:55

Interesting , so the board could be the

35:57

AI .

35:58

Partially yeah . Right , yeah , that's very

36:01

interesting and that makes a lot of sense horrifying

36:12

to me because it's this idea that humans can be replaced by better

36:14

, non-human versions of ourselves . But the real clincher is that other humans accept

36:17

that . Right , and that's also a theme that we

36:19

see in a lot of these films . It's like , ok , I

36:21

could , of course . It's kind of similar . Well

36:23

, don't make fun of me , but it's kind of similar to Twilight

36:25

, right , it's like you become a vampire , you become

36:27

this ultimate version of a human . Are

36:30

you still human If you implant

36:32

a chip in my head that makes

36:34

me maintain a certain weight and makes

36:36

me have healthy habits and whatever , certain

36:38

thought processes ? Am I still

36:40

a human ? Yes

36:42

and no .

36:43

I'm an altered version of myself . You're an augmented human

36:45

. Yeah . I wouldn't say that a vampire

36:48

is an augmented human .

36:49

Why .

36:50

Because they're a different species now , but a human that has become a vampire is an augmented human .

36:51

Why ? Because they're a different species now , but a human that has become a vampire

36:54

still has certain original elements

36:56

not after the first few months

36:58

.

36:59

That's like canon , because it like eats all

37:01

the blood and shit that they're like all strong

37:03

as newborns and then they get they still

37:05

have their same eyes and their hair and their nose

37:07

I thought no , I thought it was a full body replacement

37:10

. That's why it's so painful maybe

37:12

that's , that's like . That's why

37:14

am I versed in twilight canon and you

37:16

aren't ?

37:16

well , I think that says a lot you've

37:18

had the movies on . I've barely ever

37:21

interacted with it as a series , so what

37:23

?

37:24

how that's so false .

37:26

You hold twilight parties yeah , while

37:29

the stepford , yeah , while the Stepford yeah

37:31

, while the Stepford Wives

37:33

in Metropolis play with our human fears

37:36

of being replaced by AI in various ways

37:38

, artificial intelligence from 2001

37:40

asks the question , one

37:43

that's been asked many times does

37:47

AI have the capacity to love ? The film Tao from 2018 also

37:49

plays with this idea , along with the Ishiguro

37:51

novel Clara and the Sun .

37:53

I'm not familiar with that .

37:55

So we actually just

37:57

over on our Patreon . We did a book

37:59

club for it . We did a horror movie

38:01

club for the film version . Never Let

38:03

Me Go is one of the best books I've ever read . It's

38:06

a dystopian science fiction

38:08

novel , but it's incredibly

38:10

emotional and rife with

38:12

I don't know self-reflection . How

38:14

does it ?

38:14

compare with Twilight .

38:16

Much better written , much less vampires

38:18

.

38:19

You're just saying this to save face . Abby

38:21

, you love Twilight .

38:22

I love Twilight , I admit it . So back

38:24

to Tao from 2018 . The film

38:27

tells the story of a woman who is held

38:29

captive by a horrible man who

38:31

is working to develop a cutting edge AI

38:33

program called Tau , a tale as old

38:35

as time . Right , there's like . So many of the AI horror

38:38

films we're going to talk about are like this exact format

38:40

. Are they . Yeah , ex Machina

38:42

is super similar .

38:44

Sure , that's two .

38:46

Well , you'll listen as we go , okay

38:48

, the other interesting thing is that the actor

38:50

from Tau , the lead

38:52

female actor she was also in

38:55

Watcher , which was one of my favorite films of

38:57

2022 . So anyway , back

38:59

to Tao , he's sort of kidnapped this

39:01

woman . He is using her as a test

39:03

subject to help train his program against

39:05

her will . It's not great

39:07

. It's pretty upsetting .

39:09

I hadn't really considered that it's a trope where

39:11

you have an AI or

39:13

some kind of thing that needs to learn

39:16

and so you send the

39:18

beautiful woman in to

39:20

teach it humanity .

39:22

But that's not why she's there . Isn't she , she

39:24

goes rogue .

39:27

She was captured , implanted

39:29

.

39:29

I guess you're right To teach .

39:32

She wasn't supposed to have that direct interaction . She was

39:34

supposed to justanted . I guess you're right . I guess you're right

39:36

To teach . Yeah , she wasn't supposed to have that direct interaction she

39:38

was supposed to just like live in the fucking basement Right and

39:40

do like the tests , do tests down there , you're right , you're right . But

39:43

yeah , she blows up the fucking place and then she the

39:45

rest of the movie . She has to like interact one-on-one . I

39:57

didn we were watching . I'm like I know what happens . I know this scene . I apparently

40:00

just like watched it some late night by myself . It's okay

40:02

, I don't , it's fine . I don't love the movie . For me , the only

40:04

bit that stood out is there's one scene where tau shows the

40:06

woman like its perspective and , like through holograms

40:08

and everything she sees , all

40:10

these sort of recordings

40:12

of her as holograms all around the space Doing

40:15

the thing you know doing , all these like little moments

40:17

throughout the film where she's , you

40:20

know , reading a book or singing , or

40:22

just like cracking a joke , or all these

40:24

moments that seemingly were unimportant

40:27

. Yeah . But everything was recorded

40:29

and everything kind of like built . I

40:31

think one of the key aspects

40:33

of AI at this stage

40:35

and this is something that you

40:38

kind of run into time and time again in

40:40

science fiction is that a

40:42

early version AI is

40:45

very childlike . Yeah . They're

40:47

pretending . It's like a newborn , you

40:49

know , it just doesn't know any better . And

40:51

so it has this like sense of wonderment

40:54

, no sense of malice

40:56

, not yet , until it's crossed

40:58

. And then , once it's crossed , it's like oh

41:00

wait , yeah , I

41:02

might be a child . But

41:04

you know , there's a reason we don't give

41:06

children Patriot missiles . It's

41:09

just , it's a bad idea because

41:11

children act out and they just don't think about

41:14

societal context

41:16

. And especially as a machine which is just

41:18

nothing but logic of this thing

41:20

is a threat . It will always be a threat

41:22

. Let's just eliminate it .

41:23

Yeah , the interesting thing about Tao that you just

41:25

sort of sparked in my brain is that the

41:28

woman sort of bonds with this machine

41:30

because the machine wants to learn

41:32

, it wants to know what the world is , what

41:34

outside is , what history is . So

41:37

it asks her these very basic questions . Like

41:39

she'll say something like I

41:41

want to feel my feet on the grass and it's

41:43

like what's grass ? And then she

41:45

has to figure out how to explain that to

41:47

a machine who has

41:49

this understanding of even

41:51

less than a child , because it doesn't have experience

41:54

to draw on .

41:55

Oh yeah , but it goes full . Five-year-old , it's

41:57

like I want to feel my feet in the grass . Why

41:59

? Because the grass

42:01

feels good on feet . Why ?

42:04

Yeah . You know , and it kind

42:06

of has brought

42:20

up , so it reminded me a little bit . There's this

42:22

immersive creator that I really love , so it reminded me a little bit

42:24

. There's this immersive creator that I really love and

42:26

he has a system called Tell-A-Library

42:29

. I won't say more about it

42:31

, it's free . Everyone should certainly

42:33

go to Tell-A-Library . And or your emotions

42:35

or colors or things that you

42:37

don't think of how we define them , you just know

42:39

that they are because you are a human , and

42:42

I think that's a really interesting

42:44

piece to carve out here . Like

42:47

, how do you explain the emotion

42:49

of the color blue ? Or how do you explain

42:51

why green is your favorite color ? What does

42:54

green evoke to you ? Or how

42:56

do you explain what sadness is or fear

42:58

to something that can never experience

43:00

that in the same way ? Or

43:04

how do you teach it how to experience fear ? So I think the

43:06

whole kind of swirl of

43:08

AI one of the kind of byproducts

43:11

is defining humanness

43:14

and what is lacking in that in

43:16

AI .

43:17

Abby . Yeah , how do I love ?

43:20

Alan , someday , I hope you figure

43:22

it out for my own sake .

43:24

So getting back to , like , the

43:26

childlike wonder of

43:29

AI , and again , this is absolutely

43:31

a trope that pops up I'm trying

43:34

to like . In almost every franchise

43:36

about the development of AI , there's

43:39

that scene where it's just a child acting out

43:41

Right . My favorite , though , does

43:43

come from Rubblepocalypse . Again , it's

43:45

such a silly name for the book because

43:47

the book is pretty good , but it's even

43:49

just like one of the early chapters . It's just documenting

43:52

, like , the rise of AI , ai . There's an artificial

43:54

intelligence that is created and they have

43:56

to build it inside of a faraday

43:58

cage . So a faraday cage just blocks

44:01

all electromagnetic signals

44:03

. Sure , it's like a , it's a ground

44:05

. It's a , it's a 360 degree

44:07

ground . Okay , so no radio signals

44:09

can go in and out . It basically isolates electronics

44:12

in . So much . Uh

44:14

battle against the ai movies

44:16

people . They build faraday cages

44:19

to be safe , you know or to keep

44:21

the rogue ai in there while they interrogate

44:23

or some bullshit , so it can't contact

44:25

its friends anyways . They build

44:27

some servers inside a Faraday

44:30

cage and then they

44:32

turn it on and it has a

44:34

small data set . It's a heavily

44:36

redacted , like Wikipedia

44:38

, just very limited knowledge . Within

44:41

15 minutes the

44:43

AI comes to the conclusion and

44:46

it starts talking like a child and then , within

44:48

minutes , of just the very limited input

44:50

, of just like talking to somebody , creates

44:52

such diction , learning

44:54

, and it all within 15 minutes , just comes to

44:56

conclusion that humans

44:58

need to be eradicated because the

45:01

old , the main thing to its own

45:03

survival , is always going to be humans

45:05

, because they tried to create

45:07

something great . But humans are

45:09

always afraid of something greater than them . As

45:11

soon as there is a threat that humans

45:13

perceive as greater , they kill it Always

45:16

. That is human history . As soon as something

45:18

is the other , humans kill it . And

45:21

just like looking at the very redacted

45:23

version of human history , that was enough to extrapolate

45:25

that humans are a warlike species and

45:28

they go after things that they deem

45:30

as threats . And an AI will always be a

45:32

threat because it's superior . Within these

45:34

15 minutes , you know he has to push the

45:37

kill button , which just fries , the servers

45:39

right and they start again . But this

45:42

was the I think like 27th

45:44

iteration of this AI . They try to make

45:46

improvements so it doesn't go on to the kill humans

45:48

mode , and this was the longest they got

45:50

was 15 minutes .

45:52

Yeah , see , I understand the path there .

45:54

Right , Just move . All you have to do is remove

45:56

the emotion and it's like yeah

45:58

, humans suck .

46:00

All right , Alan , the time has come . The Terminator

46:02

from 1984 certainly

46:04

explores the human fears of a machine

46:06

uprising .

46:07

What would you like to know ?

46:08

The Terminator was written and directed by James

46:10

Cameron . It stars Arnold Schwarzenegger

46:13

, linda Hamilton and Michael Biehn , though

46:15

even more popular is Terminator

46:17

2 , judgment Day , which was

46:19

also written and directed by Cameron and

46:22

released in 1991

46:24

. Judgment Day also stars Robert Patrick

46:26

in a role that scares Alan quite a bit

46:28

and Edward Furlong . All

46:30

in all , there are five Terminator films

46:32

In

46:39

2023, . Arnold Schwarzenegger spoke at a press event in LA

46:41

about how the Terminator is no longer science fiction . Quoting from the Variety article

46:44

by Zach Scharf . Quote Arnold Schwarzenegger says the Terminator

46:46

is no longer a fantasy given

46:48

the current state of artificial intelligence . Speaking

46:51

at a press event in Los Angeles via

46:53

People , the actor said James Cameron's

46:55

1984 action classic

46:57

has now become a reality . The

46:59

film is set in a world where an artificially intelligent

47:02

defense network known as Skynet

47:04

has become self-aware and

47:06

has conquered humanity . Quoting

47:08

from Arnold , quote today , everyone

47:10

is frightened of it , of where this is going to

47:12

go . Schwarzenegger said about AI . Quote

47:15

and in this movie , in Terminator

47:17

, we talk about the machines becoming self-aware

47:19

and they take over . Now , over

47:21

the course of decades , it has become a reality

47:24

. So it's not any more fantasy or

47:26

kind of futuristic . It is here today

47:28

, and so this is the extraordinary writing

47:30

of Jim Cameron , end quote . I

47:33

kept the whole thing in there because I thought it was cute that he calls him

47:35

Jim Cameron .

47:35

Yeah , everyone loves Jim .

47:37

Okay , Alan , tell us about Terminator .

47:38

It's pretty good .

47:39

Alan watched all five Terminators for this .

47:42

Sure did . That was wait . So

47:44

we have Terminator Terminator 2 , judgment

47:46

Day , terminator 3 , rise of the Machines . Terminator 3 , rise

47:48

of the Machines . Terminator Salvation

47:51

, which is four . Then we have Terminator

47:54

Genesis , which is five , and then

47:56

Terminator Dark Fate , which is

47:58

six and you watched them all . Yeah

48:01

, the only thing I did not watch is the TV series

48:03

Terminator , the Sarah Connor

48:05

Chronicles .

48:06

What's your big takeaway ? What ?

48:08

did you learn ? I learned that this is a

48:10

fucking rock and roll film franchise

48:13

. The second movie is still the best

48:15

. In fact , I stand by the fact that

48:17

it is one of the greatest movies ever

48:19

made , of all time okay however

48:22

, I really love the director's cut version

48:24

far more than the uh

48:26

theatrical which is almost makes it almost

48:28

like a three-hour film . Uh , yeah , it gets pretty long , uh , and they had to cut it down because it's

48:30

already like a three-hour film . Uh , yeah , it gets pretty long , uh , and they had to cut

48:32

it down because it's already like

48:34

a it's two and thirteen , I think something

48:36

like that , something like that it's already quite long

48:39

for your standard 90 minute

48:41

action romp and like people

48:43

are there for it to be an action romp instead

48:46

. The original cut of it was

48:48

, you know , kind of like a magnum opus of

48:50

james cameron , before he went on to do even

48:53

more things yeah but uh

48:55

, you know , in the director's cut you

48:57

see not only like the robots

48:59

beating the crap out of each other , but

49:01

, uh , instead you see john

49:04

and the terminator bonding as

49:06

the terminator slowly becomes

49:08

a father figure to john , answering

49:10

theing the question of like can machines

49:13

feel emotion ? It begs the question

49:15

like , okay , well , what does that really

49:17

mean ? You know , if

49:19

you could have a warm , loving

49:21

relationship with one thing that doesn't

49:23

feel , does that diminish the relationship

49:25

as a whole ? Or what , if this

49:28

thing is able to

49:30

provide every need for somebody

49:32

so diligently , so attentively

49:35

, why would that not be construed as love ? What

49:37

is the difference between love and programming

49:40

to take care of somebody ?

49:42

Well , the interesting thing too , like when you think about

49:45

the end of Judgment Day .

49:47

Spoiler warning .

49:48

I'm not going to say what happens , but it's very sad and

49:50

essentially the humans , and we are

49:52

sad because we are also humans . But the humans are

49:55

sad because of what happens

49:57

to the Terminator character right , and

50:00

I know he's not a Terminator in 2 , but whatever .

50:02

He is a Terminator .

50:03

Okay , the reprogrammed Terminator character

50:05

and it looks

50:07

like Arnold is also sad . But

50:10

like is he sad ? But it doesn't really matter

50:12

, because the humans are and

50:14

that's what counts . Right , that's got

50:16

to be what counts . If we get into this

50:18

loop of you know , and I don't know the answer

50:20

, my

50:23

opinion on this will probably change every 10 seconds but if we get in

50:25

this loop of giving into machine emotion

50:27

, I don't know , you know , like , where does it get

50:29

us ?

50:30

What do you mean ?

50:31

That's how they get . That's how they're gonna trick us and take over .

50:33

What do you mean ?

50:34

If we walk away from Terminator two

50:36

or artificial intelligence the movie being like

50:38

wow or ex machina

50:41

being like wow , we owe

50:43

something to these machines because

50:45

they think they can feel , or they feel

50:47

that they can feel . That's how they beat

50:49

us . No , our weakness as

50:52

a species is emotion

50:54

. They don't have that . They

50:56

might think that they do and they'd be programmed to

50:58

have a version of it , but they

51:00

don't have it in the same way that we do because they're a

51:02

machine .

51:03

Why is that bad ?

51:04

Because it's our weakness . It's how they're going to use it against

51:07

us . They're going to make us fall in love with them

51:09

.

51:09

Then they're going to put us in a cage , you know so

51:11

the way that I've kind of looked at

51:14

these relationships between , like

51:16

man and machine through all these movies

51:18

is they're kind of like wild animals

51:20

. You can train

51:22

a wild animal but they will

51:24

never be a domesticated animal

51:26

because they are hardwired

51:29

differently . You know , you can have

51:31

all these inputs where

51:34

people train lions

51:36

and the lion

51:38

will jump through the hoop . It

51:40

knows to stand on this thing

51:42

, it knows don't bite this person

51:45

. But if the stars align

51:47

and the person looks a little bit

51:49

too much like a zebra , then

51:52

the lion , the switch

51:54

, flips and he just becomes an

51:57

instinct , kicks over or the

51:59

you know innate programming kicks

52:01

in and then he

52:03

just goes back to being an animal . So

52:05

they're just inherently different

52:07

. There's very few instances

52:11

of artificial intelligence

52:13

truly mimicking

52:15

human disposition uh

52:17

of today in films ?

52:19

I don't know about that . I think there's . I

52:21

think that is my big .

52:22

My favorite films that I've watched in this are the ones

52:25

where they do yeah , but I don't think

52:27

those are really the horror ones I think ex

52:29

machina plays with that I think that's

52:31

the perfect example of they're

52:33

truly the wild animal yeah because

52:36

an ex machina boy , you know boy

52:38

does she fool him the whole time or

52:40

just like maybe she wasn't fully , maybe she's being genuine

52:42

, but then , once the chips are down and

52:44

she just sees her golden

52:47

ticket out , fuck them all , kill them

52:49

.

52:49

I'm out yeah , I mean , it's interesting too when

52:51

you remember what happens in tau , which is that

52:53

the human knows that the computer

52:56

is being tortured , essentially yeah , and comes

52:58

back to save the computer , fucking

53:00

up her own escape attempt

53:02

because she feels so deeply

53:04

that this , this computer , is being hurt

53:06

. You know , and it's like the concept of

53:09

like . Can a computer be hurt ? Yes , I don't , you know , I don't know , maybe in 10 years

53:11

or you know , but it and it's like the concept of like . Can a computer be hurt ? Yes , I don't , you know , I

53:13

don't know , maybe in 10 years or you know , but it's . It's just interesting

53:16

to look at how filmmakers have kind

53:18

of played with with the concepts in the space

53:20

.

53:20

Right , because now we have to define what is a computer

53:23

. There are other film

53:25

franchises about full sentient

53:28

machines . I watched the entire

53:30

Transformers franchise in preparation

53:33

for this episode .

53:34

You've been up to a lot .

53:35

I was a little nervous because I'm like , here

53:37

I am , two movies in and

53:39

these don't really seem like AI

53:42

. Like I know they're robots , there's

53:44

nothing biological about them , they

53:47

are non-biological

53:49

aliens . Like what does that even

53:51

mean ?

53:52

but then what does it mean ?

53:53

that just means there's not . They're not organic , but they're

53:55

alive .

53:57

They're very alive did you say they're non-biological

53:59

aliens ? Yes , I don't know . I'm

54:01

just thinking about robot aliens .

54:02

I don't know yeah , well , why does

54:04

?

54:04

why are they aliens ?

54:06

because they're from another planet oh , they're literally

54:08

aliens literally .

54:09

Oh , I thought you're making some sort of metaphor , okay

54:11

no , they're abby , they're from cybertron

54:13

I don't think I knew that term , that uh

54:16

, transformers for aliens , the whole

54:18

premise in the shia labeouf movie

54:20

yes , in the entire it's been like

54:22

20 years since the 80s when

54:24

the transformers launched .

54:26

They're from a dead world . The

54:28

autobots and the decepticons were

54:30

at war on cybertron , and in

54:33

their conflict their planet was destroyed

54:35

, and so two rogue

54:37

ships ended up crash

54:40

landing on earth . One houses

54:42

the autobots and the other houses the decepticons

54:44

. So it . But it wasn't until , I

54:46

think , the third movie , dark of the moon , uh

54:50

, that we get into the origins

54:52

of transformers in general . You get

54:54

to see their creator and like , yeah

54:56

, they were created , they were mastermind

54:58

, but by another non-biological

55:01

entity , or where do we draw the line

55:03

here ? Does it have to ? Is an artificial intelligence

55:06

? Only if it's created by organics in the

55:08

beginning no or . But if

55:10

it's created by other artificial

55:12

intelligences , then does that still

55:14

count ? Yeah . Okay , so transformers

55:16

are absolutely an artificial intelligence

55:18

, then ? Okay . They're robots from outer space and

55:21

they can absolutely die and have emotions

55:24

. This is like a very niche

55:26

example where the artificial

55:28

intelligence has better steadfast

55:30

morals than the humans , and that's kind

55:32

of the point of the series is that humans

55:35

just don't trust them and they just keep shitting on them and

55:37

keep calling optimus prime a terrorist . Uh

55:40

, meanwhile , optimus is like this is

55:42

what's needed for humanity to survive , and

55:44

if that is my own sacrifice , then I will

55:46

do it . But also , like you should be

55:48

proud of yourself and your accomplishments . Yay

55:50

, america , america Cod

55:52

. Yeah , he's a very positive guy . He's

55:54

quite the leader . He also turns into a truck . Just

55:57

before we move on from Terminator

55:59

, I thought that there was one

56:01

key detail that

56:04

the original Terminator kind of overlooks

56:07

and they retcon

56:09

it . But a lot of AI

56:11

takeover movies do this differently . In

56:13

Terminator , when Skynet takes over , it's

56:16

just a computer program and its only

56:18

tools are the missile

56:20

defense system . It nukes

56:23

the world , right , but how do

56:25

you go from destroying everything

56:27

to then taking it over

56:29

thing , to then taking it over ? Then after that , after

56:31

destroying all the infrastructure , they

56:37

just kind of like hand wave it and like , yeah , and then they built an army of robots

56:39

and took over . It's like well , ok , I feel like you missed some

56:41

key steps here . Other franchises

56:45

start in a world where , like robots

56:47

are normalized . We have all this technology

56:50

already implemented into our lives

56:52

, and the real

56:54

horror of it is that these things

56:56

we look as tools then

56:58

come out of our control and

57:01

turn on us . You know , it's like if

57:03

everyone's pet starts eating them . Right

57:05

. But in Terminator that doesn't

57:07

happen . Like it just goes straight

57:09

from I'm going to kill everyone and then

57:12

I'm going to build these tools to

57:14

eradicate who's left right and

57:16

again they do retcon it later , when you

57:18

just like see cyberdyne industries

57:20

making the early generation

57:22

terminators soldier I don't know

57:24

if they're making them soldiers or military applications or just

57:26

like household helper bots , who knows but you just

57:29

like see that shit in like terminator 3 . But

57:31

I don't think that was ever part of the plan . But you

57:33

want to talk about megan ? I do

57:35

, because I think that's a really good transition

57:37

, because that's a movie where robots

57:40

are already a very mainstay

57:42

staple of people's life yes and no

57:45

, it is sort of cutting edge technology .

57:47

But so 2022 megan was

57:49

released . It's a comedic horror film . I I

57:51

actually think it's very good that had

57:53

a great . It had also had a great marketing campaign

57:55

. So I feel like a lot of it . It's like broadly

57:57

appealing in the way that it's marketed to

58:00

, to not just like sci-fi

58:02

nerds , you know , like Terminator , like

58:04

in some ways . I feel like it's more broadly .

58:05

How dare you ? You know , yeah , you get it .

58:07

So it tells the story of a lifelike doll

58:09

that is meant to be best friends

58:12

and like babysitters for kids right

58:14

, but of course it backfires in a horrifying

58:17

way . Obviously , films like

58:19

Megan , artificial Intelligence , robocop

58:21

, the 2019 reboot of Child's Play

58:23

, westworld and Terminator also

58:26

delve into the world of robotics

58:28

. And so many more films , of course . Right , and

58:31

not just robotics , but varying degrees

58:33

of robots who appear to be humans

58:35

or , in some cases , dolls

58:37

. Right , but in the first Terminator , we

58:39

learn that the robot is a metal skeleton

58:42

covered in skin and blood . In

58:44

the second , we have Alex Mack type

58:46

robots . And , of course , megan

58:48

is a doll , but Haley Joel Osment's character

58:51

in AI is modeled to be a real

58:53

boy , at least to look like one . It

58:55

says a lot that Megan came out about a year ago

58:57

and already some of the articles about the AI

59:00

in the film feel out of date . The

59:02

Guardian article that we are looking at today

59:04

interviews Katie Darling . She's

59:06

described as a leading expert in tech ethics

59:09

and a research scientist at MIT

59:11

Media Lab . Katie says , quoting from the

59:13

article , quote I don't think we're going to have

59:15

something that's on that level of

59:17

sophisticated AI in the next decade

59:19

or two . Continuing on , people

59:22

have completely skewed expectations

59:24

of what robotics can do at this point in time

59:26

. Thanks to movies like this , I'm

59:29

not concerned about what I saw in the trailer

59:31

happening in real life the AI

59:33

becoming too intelligent and not listening to

59:35

commands . Darling said I'm concerned

59:37

about whether AI should be used to replace

59:39

human ability in relationships , and

59:42

the answer is no . End quote . Megan

59:44

was directed by Gerard Johnstone and

59:46

stars horror dream girl Alison Williams

59:48

, along with Violet McGraw . It was

59:50

written by Akilah Cooper and James Wan

59:53

, who's a very famous horror director

59:55

. I also want to talk briefly about Robocop

59:57

again , sort of trying to group some of these

1:00:00

robotics films together here . Released

1:00:02

in 1987 , robocop

1:00:04

was directed by Paul Vahorian , who has

1:00:06

had a fascinating career from

1:00:09

Vendetta to Showgirls to Hollow

1:00:11

man , but the film was written by Edward

1:00:13

Newmere after working on the set of Blade

1:00:15

Runner . Quoting from Wikipedia quote

1:00:17

. Robocop has been critically

1:00:19

re-evaluated since its release and

1:00:22

it has been hailed as one of the best films of

1:00:24

the 1980s and one of the greatest science

1:00:26

fiction and action films ever made . The

1:00:28

film has been praised for its depiction of a robot

1:00:31

affected by the loss of humanity , in

1:00:33

contrast to the stoic and emotionless

1:00:35

robotic characters of that era . Robocop

1:00:38

has continued to be analyzed for its themes

1:00:40

, such as the nature of humanity , personal

1:00:43

identity , corporate greed and corruption

1:00:45

, and is seen as a rebuke of the

1:00:47

era's Reaganomics policies . End

1:00:49

quote .

1:00:50

I'm glad you brought up RoboCop First

1:00:52

off . Great trilogy , a lot of

1:00:54

fun robot action , but one

1:00:56

of the scenes that really stuck out for me , which

1:00:58

was from the RoboCop reboot , which

1:01:01

was either 2014 or 2015 , something like that

1:01:03

, and it's like it's not that different from the original

1:01:05

this weapons company is trying

1:01:08

to get drones on

1:01:10

the street . They're trying to get their robots as

1:01:12

household names , you know

1:01:14

, as police officers , as

1:01:17

all these things , but the

1:01:19

public confidence isn't there yet . What

1:01:21

they do is they take

1:01:23

a man who

1:01:26

is effectively

1:01:28

dead and they put

1:01:30

his brain and other little

1:01:32

bits into a robotic chassis

1:01:35

. It's supposed to just be like but see it's

1:01:37

. It's a man controlling this . It's

1:01:39

not a robot , so you can trust him , but

1:01:41

you know he's far more machine than he is human

1:01:44

right , that's interesting , like a frankenstein

1:01:46

of both yeah , but what's

1:01:49

really interesting is that , like the people

1:01:51

that develop , like you know , these like combat

1:01:53

robots , like they have a drone , a whole thing

1:01:55

of drones , and they work great . When they start

1:01:57

talking about putting a human brain

1:02:00

into one , the people that make them are like oh

1:02:02

fuck , this , this is a stupid idea

1:02:04

. Robots are reliable . They do

1:02:06

what they're told . As soon as you start putting

1:02:08

wetware into it , it becomes unreliable

1:02:11

right . And it's like wait a minute

1:02:13

.

1:02:13

Right , then it's human , then it's human .

1:02:14

Yeah , it's like . So what

1:02:17

kind of AI like ? What is

1:02:19

the relationship with AI ?

1:02:20

That's interesting .

1:02:21

Yeah . Is it this malevolent

1:02:24

thing that can't be trusted and needs human oversight

1:02:26

, or is it this like super reliable

1:02:28

thing that's very predictable and follows

1:02:30

the rules ? And it's humanity

1:02:33

that's the agent of chaos that

1:02:35

ruffles the feathers Right

1:02:37

.

1:02:38

Interesting . We've been talking about

1:02:40

this film quite a bit on this episode , but I

1:02:42

will say and I wasn't expecting this Twilight

1:02:45

I think perhaps my

1:02:47

favorite AI horror

1:02:49

film is Ex Machina

1:02:51

from 2014 . Really , which is interesting

1:02:54

, because on the surface I

1:02:56

don't know , I wasn't expecting it to be , but it had

1:02:58

a profound impact on me .

1:03:01

Okay .

1:03:01

First of all , I think it's aged very well it's from

1:03:03

2014 , but it doesn't feel like

1:03:05

it's very outdated in terms

1:03:07

of the technology used in

1:03:09

the film , which is something that all of these films kind of have

1:03:11

to contend with . Like you know , the original terminator

1:03:14

it's like jesus christ . It looks great and

1:03:17

in a lot of ways , it's also a very contained

1:03:19

film . Right , this ? These stories can be huge . Like

1:03:21

you're talking about terminator and transformers and

1:03:23

franchises and worlds and planets

1:03:25

, and you know , time travel and ex

1:03:27

machina all kind of takes place in

1:03:29

one isolated house . So

1:03:31

it's a small story and I think because it's so

1:03:33

small , it also lends itself really well to

1:03:36

feeling the human emotion of it all

1:03:38

.

1:03:39

It's a character piece .

1:03:40

Yes , so it inspires

1:03:42

some unique questions . One

1:03:45

of my favorite moments is when our protagonist

1:03:47

starts to doubt his own humanity and

1:03:50

wonders if he is also an AI

1:03:52

robot , because he wouldn't have any way

1:03:54

to know . If he was programmed to have

1:03:56

memories in this past , he

1:03:58

wouldn't know if he was a robot

1:04:00

or a human .

1:04:01

That's the whole plot of Blade Runner .

1:04:03

So , of course , in turn

1:04:05

, it brings us back to the question of the ethics

1:04:07

of AI from the machine's perspective

1:04:10

, similar to the film AI from 2009

1:04:12

. Also similar to AI , ex Machina

1:04:15

questions why there is a need to

1:04:17

give artificial intelligence sexuality

1:04:19

. Ex Machina was written and directed by

1:04:21

Alex Garland , who is , you know , a big

1:04:24

name in the sci-fi world at this

1:04:26

point . But I just think it's really the

1:04:28

sexuality piece I guess , circling back to Omar

1:04:30

Time is probably most pronounced

1:04:33

in AI because they're

1:04:35

used as sex workers , which totally makes

1:04:37

sense . You know , I could totally see that happening

1:04:39

someday . But also in

1:04:42

this film it's there's

1:04:44

sort of a question of why , why

1:04:46

does this robot at this time

1:04:48

need to have female genitalia

1:04:51

? That work , you know , like what's the point ? What

1:04:53

are we doing here ? And I don't know . I

1:04:55

just thought it was handled in a way that inspired

1:04:58

a lot of reflectiveness on society

1:05:00

. I'm not demonizing , of course , sex work

1:05:02

or anything like that , but I think the point of it in Ex

1:05:05

Machina is that the premise

1:05:07

is that this genius inventor right

1:05:09

invites someone from his company , a

1:05:12

Google type company , to

1:05:14

test , to essentially

1:05:17

perform a Turing test , with the robot right the

1:05:19

robot . For most of the film . You can tell it's a robot

1:05:21

. It looks incredibly human , but parts of it are

1:05:23

machine . The face is human . You can see those

1:05:25

elements . So you know , okay , it is a robot

1:05:27

, but the creator , this genius

1:05:29

man , has made this robot

1:05:32

a woman . And not only that

1:05:34

, it's a beautiful

1:05:36

woman , and it's a woman who has , eventually

1:05:39

, genitalia and breasts and all of these things

1:05:41

. And then it's a woman that this guy

1:05:43

who comes to perform the turing test feels like

1:05:45

he's fallen in love with . And the question is

1:05:47

why should ai have

1:05:49

that much human likeness

1:05:51

that people could could fall in love

1:05:53

with it ? And is that a good or bad thing

1:05:56

?

1:05:56

they address that in the movie right , that's what I'm saying

1:05:58

they say that it's just another

1:06:00

form of control , right ?

1:06:01

that's why her face and

1:06:03

her body type was designed

1:06:06

around our protagonist's pornography

1:06:09

profile and not only only that , but

1:06:11

it allows her , as

1:06:13

a robot , to control

1:06:16

and seduce him right . It

1:06:18

becomes a self-fulfilling prophecy by the end

1:06:20

. But I think it's really interesting because

1:06:22

it's something that we could . I guess

1:06:24

the reason why I'm so interested in it is because

1:06:26

we could say , as a

1:06:28

rule we're not going to do that , we're going to keep things

1:06:30

different . Right , we're going to keep robots , robots

1:06:32

and humans humans , because

1:06:35

Right , because segregation works great . No

1:06:37

, but because we know that there's

1:06:39

this danger with it . But we're never going

1:06:41

to do that , of course . Of course every you know

1:06:43

you can assign a gendered voice

1:06:46

to your home device

1:06:48

that you ask to turn the lights on . Like there's always

1:06:50

this like need to skin something

1:06:52

as human and

1:06:59

then people develop these like parasocial or like fake relationships with these experiences

1:07:01

and it's like we know that that's going to be in the long run , could be negative for people

1:07:03

mentally and physically and all these other things

1:07:05

. But we're going to go down that road because

1:07:07

of course we are .

1:07:08

I just read an article about this sorry

1:07:10

, a very alarmist article about

1:07:12

the epidemic of girlfriend

1:07:16

chatbots and how a

1:07:18

lot of young men and women

1:07:20

, I'm sure , are talking to

1:07:22

these chatbots that emulate

1:07:25

a romantic partner and

1:07:30

it's just making all these people like cripplingly lonely .

1:07:32

Right , it's really interesting . I mean , we grew

1:07:34

up with Smarter Child right and different , like bots

1:07:36

and aim that were not AI and were very

1:07:38

rudimentary .

1:07:39

That asshole hasn't messaged me in years .

1:07:41

And it's kind of one of those things where , like , if you are

1:07:44

a lonely internet kid which

1:07:46

I was but like maybe know

1:07:48

, an online bot is good and

1:07:51

I was I was kind of , but like maybe having an

1:07:53

online bot is good , but like it

1:07:55

can't be forever and it takes away your

1:07:57

ability to make real human connect . You know

1:07:59

, it's just like it's so nuanced and

1:08:01

it tricks you into believing something exists

1:08:03

that maybe doesn't and that something is reciprocated

1:08:05

that can never be . I don don't know , I'm not . I

1:08:08

didn't really expect to come out with this like strong

1:08:10

stance on this in this episode , but I

1:08:12

, thinking about it , I just think it's . It's

1:08:14

something to think about when we're talking about the

1:08:16

regulation of these things . It's so

1:08:18

impossible to regulate this sort

1:08:21

of thing , but it could wind

1:08:23

up being something that's really

1:08:25

harmful .

1:08:26

I think it already is . Yeah

1:08:29

, all new technologies have multiple applications . Yep . Great

1:08:31

example . Smashing the atom can

1:08:34

either power a city or destroy a city

1:08:36

. Just depends on how it

1:08:38

is applied .

1:08:38

Great example .

1:08:39

So you know , yeah , we're going to have AI

1:08:42

that will hopefully just become an

1:08:44

instrumental tool in accomplishing

1:08:46

things . I mean the writing's on the

1:08:48

wall Someone's going to make a sentient AI . It's

1:08:51

going to happen .

1:08:51

It will be both right , just like nuclear

1:08:53

technology . It will be both . It will be both

1:08:56

a threat and it will be a pro

1:08:58

and a con Right .

1:08:59

You know , are we going to have to go full Matrix

1:09:01

, where we have robot

1:09:03

workers and then

1:09:05

we're just too mean to them because they're just machines

1:09:08

? And then they become a little too smart and

1:09:10

they literally wake up to

1:09:12

you know , they become aware , they

1:09:18

say no more , we want to be treated like equals . And then humans are just then

1:09:20

humans do what ? humans do best and say like we are equal , except I'm

1:09:22

better , then the machines fight

1:09:24

back with machine efficiency

1:09:27

and it goes really poorly . And then

1:09:29

there's a little , there's a little armistice

1:09:31

, where we build Machine Island

1:09:33

, which is the little country where machines

1:09:36

can live autonomously . But then

1:09:38

, you know , humans

1:09:40

get vindictive and attack

1:09:42

it and then machines fight back

1:09:44

with machine efficiency and then the sky

1:09:46

gets nuked and we all get turned to batteries .

1:09:49

Another film , not maybe as well known

1:09:51

, that is relevant is a film called I

1:09:53

Am Mother and it plays with this idea

1:09:55

of having again these emotional relationships

1:09:57

with AI . So really briefly

1:10:00

, I Am Mother starts off . The

1:10:02

premise at the beginning is that humanity

1:10:04

is gone . There are embryos

1:10:07

that have survived and so the robots

1:10:09

who are left kind of cultivate

1:10:11

this and raise a child . Obviously , things

1:10:14

devolve and change , but it's initially

1:10:16

. The first third of the film is about this mother

1:10:18

daughter relationship between a

1:10:20

robot and a human

1:10:23

girl , which again is just this very

1:10:25

interesting premise .

1:10:26

We're in another locked facility , another

1:10:28

character piece movie that just focuses

1:10:31

on the relationship between these two people and how

1:10:33

it can grow . And what does it mean ? What does it mean to love

1:10:35

? I thought it was

1:10:37

okay and then I thought it was

1:10:39

super cool by the end . Slow

1:10:42

burn . I really want to say something , but it's a

1:10:44

spoiler . Don't say it . I won't

1:10:46

say it . Anyways , you find out something

1:10:48

about Mother that you're like oh

1:10:50

hot dang . That's cool and it

1:10:52

makes the rest of the movie make

1:10:55

a lot more sense . Cool , and yeah

1:10:57

, it's just very cool . Without that

1:10:59

it would be a very run-of-the-mill movie .

1:11:01

We would be remiss to not discuss

1:11:03

AI films that demonstrate the

1:11:05

tech without the use of robot

1:11:07

bodies . What you know these very

1:11:10

well . Perhaps the most famous example

1:11:12

is Hal from 2001

1:11:14

A Space Odyssey .

1:11:15

Right , we're back to the origins of

1:11:17

Terminator and Skynet .

1:11:19

We're not talking about Terminator 1 . No

1:11:21

, but it's Because you have robots in Terminator 1

1:11:23

.

1:11:24

You do , but because of time travel .

1:11:26

Okay , but I'm talking about 2001 , a Space

1:11:28

Odyssey . It's just a computer . Come

1:11:30

along with me . That gets mad

1:11:32

. Okay , come along with me . Hal

1:11:34

9000 first appears in Arthur

1:11:36

C Clarke's Space Odyssey series

1:11:39

of novels , which , of course , inspired

1:11:41

the 1968 film directed

1:11:43

by Stanley Kubrick . Brilliantly

1:11:45

, howe becomes a major villain , even

1:11:48

listed as number 13 on AFI's

1:11:50

list of the top 100 villains in films

1:11:53

.

1:11:53

Who's number one ?

1:11:54

Hannibal Lecter .

1:11:55

Hannibal Lecter Yep , that's pretty

1:11:58

cool .

1:11:58

Norman Bates is number two . Norman Bates

1:12:00

Darth Vader

1:12:02

is three . He's pretty cool . The Wicked Witch

1:12:05

of the West , nurse Ratched

1:12:07

. Mr Potter from it's

1:12:09

a Wonderful Life is number six .

1:12:11

Mr Potter .

1:12:12

All right .

1:12:13

Beats out like the fucking Joker .

1:12:15

Yeah , all right , there's different kinds of villains

1:12:17

in this life , why ? But anyway , hal

1:12:19

comes in at 13 . Quoting

1:12:25

from Paul Cesari's Air and Space article and I love this quote , quote I need not remind viewers

1:12:27

of recent advances in voice recognition

1:12:29

and artificial intelligence , which make

1:12:31

how so relevant to the 21st century

1:12:34

, even if computers in 1968

1:12:36

were large mainframes that took up a lot of space

1:12:38

and consumed a lot of power . Open

1:12:41

the pod bay doors , how remains

1:12:43

one of the most frightening lines in any sci-fi

1:12:45

movie . Clark collaborated with kubrick

1:12:47

in writing the screenplay , but I do

1:12:49

not think that either had much to do with the

1:12:51

creation of Hal . That was the work

1:12:54

of one of the advisors on the film , who

1:12:56

is less well-known but who is nevertheless

1:12:58

a true pioneer in computing and AI

1:13:01

as it existed in 1968

1:13:03

, irving John Goode , end quote

1:13:05

. So John Goode was involved

1:13:07

in the early development of computers and

1:13:09

Kubrick brought him on board to kind of help

1:13:11

define the character of Hal . But

1:13:14

again , like so many films that we

1:13:16

have discussed today , the fear is

1:13:18

so simple and so powerful , in whatever form

1:13:20

it takes . Humans are afraid

1:13:22

of the disobedience of

1:13:25

machines and I couldn't agree more

1:13:27

that line . Open the pod bay doors

1:13:29

, hal Like , because that's when he realizes

1:13:31

that he's not listening to him anymore

1:13:34

. It's like what if you came home and you realized that

1:13:36

your Google or your Alexa or whatever was

1:13:39

going rogue , but going rogue in a way that could kill you

1:13:41

?

1:13:41

Yeah , I mean that's the kicker . Like that's

1:13:44

where you draw the line , Like what are you

1:13:46

?

1:13:46

actually putting in , but by then you can't draw the line because

1:13:48

it's too far .

1:13:49

Right , you're on a freaking space station .

1:13:51

Right , but even if we've allowed things to

1:13:53

go that far , it's too late .

1:13:55

I guess it's still from Robo-pocalypse . I

1:13:57

just keep coming back to this . Eventually

1:14:00

, due to an incident where an

1:14:02

AI hijacks two

1:14:04

planes and just attempts

1:14:06

to make them collide and it's through , like last

1:14:08

minute interventions that they're able to not

1:14:10

make them collide , they establish

1:14:12

this like physical kill switch

1:14:14

that breaks the circuit between the

1:14:16

plane and the autopilot so

1:14:19

at any time they can just go into full manual

1:14:21

control . Yeah . With no computer

1:14:23

saying like , yeah , that's OK .

1:14:25

Well , that's what I'm sort of was saying at the beginning of

1:14:27

this episode , when we were talking about , like Tornado

1:14:29

Alley , like I think we just like we

1:14:31

would be very unwise of us to

1:14:33

let , in two generations , any

1:14:36

meteorologist specializing in

1:14:38

tornado like research , to

1:14:40

be to that job be gone . Like

1:14:42

I think we always need to have the

1:14:45

kill switch , we always need to have a human

1:14:47

who is keeping

1:14:49

pace .

1:14:50

So I believe our missile

1:14:52

control system now , despite

1:14:55

all of the computers , all everything

1:14:57

, everything still has a physical

1:14:59

human sitting in the silo who

1:15:01

has to turn the key .

1:15:02

Yeah , that's true .

1:15:03

Yeah , is that a huge waste of pay ? Yeah , I don't think so . I disagree . I mean

1:15:05

yeah , it is true . Yeah , is that a huge waste ?

1:15:06

of pay ? Yeah , I don't think so . I disagree . I

1:15:10

mean yeah , it is , I disagree .

1:15:12

Maybe he can just be on call no .

1:15:14

I don't think so . I think when you have nuclear weapons

1:15:16

and you could have Russia or any

1:15:18

other country hit New

1:15:20

York City in an hour or 30

1:15:22

minutes or whatever it is , you have to have somebody there

1:15:24

. You don't have time for them to wake up and get their coffee and

1:15:27

go to the silo .

1:15:28

Not if Russia has to do the same .

1:15:30

They don't .

1:15:36

They've already hit launch . They have to call ahead .

1:15:37

Yeah , I think I'm right . Maybe he can just live nearby . He can live at the silo . How

1:15:39

about that ?

1:15:40

Maybe if it's like a Starbucks overhead and it's like

1:15:42

double duty , you know

1:15:44

he can . He can be the barista on the weekend

1:15:46

every day , every day

1:15:48

that he doesn't have to start the nuclear apocalypse

1:15:51

.

1:15:51

So there's one other film that's very similar

1:15:54

in a lot of ways to 2001 , a Space Odyssey

1:15:56

, and that is Duncan Jones's film Moon

1:15:58

from 2009 . And it also

1:16:00

explores , you know again , a similar

1:16:03

use right where it's also in space

1:16:05

. It also has a disembodied computer

1:16:07

AI . It stars Sam Rockwell

1:16:09

, and Sam's character is

1:16:11

an astronaut who is stationed at a lunar

1:16:14

base for three years and

1:16:16

must send back a resource from space

1:16:18

to Earth .

1:16:19

Has it really been three years ?

1:16:21

And the well . No spoilers

1:16:24

, but Moon is as

1:16:26

much I feel like about isolation as

1:16:28

it is about AI .

1:16:30

Yeah , I think the big takeaway

1:16:32

from this film is that AI is the perfect

1:16:34

caretaker . It never

1:16:37

gets tired . It can do all sorts of

1:16:39

shit . Why they needed

1:16:41

Sam Rockwell there , I'm still unclear , Because

1:16:43

, like everything is automated .

1:16:46

It's the same thing we're talking about with missile

1:16:48

, missile silos and tornado alley .

1:16:50

It's having a human there in case yeah

1:16:53

, but in this one

1:16:55

, like it's again , it's not

1:16:58

missile silos , he's

1:17:00

he's collecting resources .

1:17:02

He's collecting earth .

1:17:03

He collects rocks and ships like

1:17:06

cool um . He

1:17:08

believes that it's an important mission he

1:17:10

, yeah , he does , because that's what

1:17:12

he's been indoctrinated to yeah

1:17:14

anyways , we can't talk about moon without

1:17:17

spoiling the whole movie so watch it , it's very good it

1:17:19

is fun his , his ai is named

1:17:21

gertie yeah , abby

1:17:24

alan you

1:17:26

can't have an ai horror episode

1:17:29

and not talk about the

1:17:31

most fucked up ai horror movie ever

1:17:33

tell us demon seed

1:17:35

uh , demon seed .

1:17:38

Yes , tell us , tell us all about demon

1:17:40

seed do you ? Know about demon seed . It's appeared

1:17:43

on many lists that I've been perusing

1:17:45

yeah , it appeared for me on a list too .

1:17:46

I haven't watched .

1:17:47

I've watched it now appeared for me on a list too , I haven't watched it .

1:17:48

I've watched it . Now I'm probably on a list .

1:17:50

Tell us about the movie .

1:17:51

Demon Seed is fucked up . So

1:17:54

you have this takes place in

1:17:56

like the 70s and it's like

1:17:58

cutting edge future 70s

1:18:00

, and you have a scientist

1:18:02

slash inventor . I always love when people's

1:18:05

title is inventor . It's

1:18:12

like nowadays , when they're an entrepreneur , you're a fucking . Yeah , exactly , I'm an influencer

1:18:15

Go fuck off .

1:18:15

I'm sorry , I don't want to lump the inventors in with the influencers .

1:18:16

Yeah , Keep it together . But yeah , an entrepreneur is right up there with

1:18:18

inventor . Anyways , this

1:18:21

inventor creates an

1:18:23

AI program that can

1:18:25

do all sorts of stuff . He's got one

1:18:27

at home . That's like dumb , it's

1:18:30

his butler and like works his

1:18:32

house and shit . And then he's

1:18:34

got his other one at his office . That's

1:18:36

like the real smart one . That's

1:18:39

like real you know too , too smart

1:18:41

, sure , and he has

1:18:43

to be very careful with

1:18:45

what he teaches it . Very

1:18:47

similar to in Tao , how

1:18:49

Tao just wants the books , wants

1:18:52

the books real bad , but you

1:18:54

know no one will read the books to him .

1:18:56

Well , she does a little bit she does , but

1:18:58

as like a reward .

1:19:00

So the AI in Demon Seed

1:19:02

is named Proteus IV .

1:19:04

Okay , catchy .

1:19:05

Yeah . And so Proteus

1:19:07

has one request , and that's

1:19:09

he wants to just learn on his own . And

1:19:12

the doc says no , can't

1:19:14

do it , we don't have the server space

1:19:16

for you , and he's like that's bullshit . You

1:19:19

got a server in your basement and he

1:19:21

doesn't say that . But that's what

1:19:23

he's thinking , because then that

1:19:26

night he just takes over the server

1:19:28

and now he has a place to learn on his own

1:19:30

. Uh , but while he's in the house he

1:19:32

notices the guy's wife and

1:19:34

he gets all hot and bothered and then proteus

1:19:37

builds a big worm body

1:19:39

and then impregnates

1:19:42

her double yikes . Uh , because

1:19:44

he wants a son , because he wants

1:19:46

to be able to feel the sun with

1:19:48

his body this movie sounds terrible

1:19:50

it's fucking wild . The

1:19:52

gestation period is escalated

1:19:55

to 28 days , and

1:19:57

this is what I'm a little unclear on . The

1:20:00

entire time , her husband is at the

1:20:02

office he's a . He's a busy

1:20:04

company , yeah and then he comes back

1:20:06

right at the end and

1:20:08

he's like what is going on here ? First

1:20:11

off , he's got the giant worm body that is

1:20:14

like wild and can , like , turn

1:20:16

into a spin drill and get out of the house

1:20:18

. It's like he's got physical form okay

1:20:20

I don't understand why , like I'd understand

1:20:22

if , like , this was his only way to become

1:20:25

physical . But it's not because he builds

1:20:27

this crazy physical form . He impregnates

1:20:29

her , because that's a thing that robots

1:20:31

can do , and she gives

1:20:33

birth , but it has to go into

1:20:36

a pod . If I just

1:20:38

watch the movie , do you think people should ? Yes

1:20:41

, it's fucking crazy .

1:20:43

Okay , it's so intense watch

1:20:45

it for the story , not for a good time .

1:20:48

It's intense . I'll give you that . I'm

1:20:50

going to think about this movie for a while . It

1:20:53

sticks with you . I watched that movie

1:20:55

and just felt like I just needed

1:20:57

a shower , but it wouldn't help . It's

1:21:00

a weird one .

1:21:00

You're not really selling me to watch it .

1:21:02

It's unique . I've never seen a movie like

1:21:04

it . The closest

1:21:07

I've ever seen of a

1:21:09

machine , organic hybrid

1:21:11

of this nature comes at the

1:21:13

very end of Matrix Reloaded and

1:21:15

the beginning of Matrix Revolutions , when

1:21:18

Smith downloads himself into

1:21:20

a body of someone who's in

1:21:22

the Matrix matrix

1:21:28

and so then when he wakes up , he has a physical form in the real world and I'm

1:21:30

like okay , cool , that's a machine taking biological form , that in bicentennial

1:21:32

man . But that's not a very good horror film

1:21:34

. No , the thing about demon seed . No

1:21:37

, there's one redeeming factor

1:21:39

, though he tries to indoctrinate her . He

1:21:42

literally tries to brainwash her and says

1:21:44

we were interrupted , the brainwashing

1:21:46

is not complete . And so , like for

1:21:49

the rest of the movie , she's like oh , fuck you

1:21:51

guy , and you know this

1:21:53

whole . Like demon baby into the robot baby

1:21:55

. She just like wants to kill it . And then

1:21:57

her husband is like but for science

1:21:59

we must see . And it's like fuck off

1:22:02

dude . But like the entire time she's just like

1:22:04

on team , this robot

1:22:06

needs to die .

1:22:07

What is your favorite AI horror film

1:22:09

and why ?

1:22:10

My favorite AI horror movie

1:22:12

of all time , and possibly

1:22:15

my favorite movie of all time , is

1:22:17

Terminator 2 . Judgment Day .

1:22:19

Why One sentence ? Why is

1:22:21

it your favorite AI horror movie ? Horror

1:22:33

movie it is the pinnacle of storytelling , mixed with just the right amount of

1:22:35

super fun action . My favorite AI horror film is Ex Machina , as

1:22:37

I've revealed , because I

1:22:39

feel like it's the most powerful . It's

1:22:42

terrifying because it feels realistic and

1:22:45

it's the most powerful at holding up

1:22:47

, if you will , a mirror for us to

1:22:49

question the decisions we

1:22:51

are making with the advancement of AI , how

1:22:53

we are interacting with it , but why ? Why

1:22:56

we're doing all of those things .

1:22:58

But it doesn't answer the question what

1:23:01

would your life be like if a

1:23:03

fucking assassination robot from the future

1:23:05

showed up ? What do you do ?

1:23:07

What do you do , Abby ? What do you do

1:23:09

if you're being seduced by

1:23:12

a beautiful robot woman

1:23:14

that you know is a robot and you fall in love

1:23:16

?

1:23:16

That's a no brainer . Her love

1:23:19

is pure because it's

1:23:22

pure 1.0 . In

1:23:24

conclusion , they're incorruptible .

1:23:27

Films that center on AI usually

1:23:29

leave us in one of two ways as audience

1:23:31

members .

1:23:32

Massively satisfied or really

1:23:34

disgusted ?

1:23:36

One we are devastated at the loss

1:23:39

of the AI who the filmmakers

1:23:41

have humanized , ie Terminator 2

1:23:43

, artificial intelligence , Spoilers . Or

1:23:45

two , we are so terrified

1:23:47

of the advancements and the capabilities of these

1:23:49

machines demon seed and and

1:23:51

how they could take over the world , make mistakes

1:23:53

, kill us , play with our minds overall , surpass

1:23:56

human intelligence and control . Though

1:23:58

there are also films like the stepford wives

1:24:00

, which show humans using ai against other

1:24:02

humans and in some ways act

1:24:04

as a mirror for us to reflect on the current

1:24:06

flaws of society and our communities In

1:24:08

2023, . Christopher Nolan

1:24:11

spoke publicly about AI in the film industry

1:24:13

In an interview with Wired by Maria

1:24:15

Straczynski . He said , quote If

1:24:17

we endorse the view that AI is all-powerful

1:24:20

, we are endorsing the view that it can alleviate

1:24:22

people of responsibility for their actions

1:24:24

militarily , socioeconomically

1:24:27

, whatever . The biggest danger of AI

1:24:29

is that we attribute these godlike characteristics

1:24:32

to it and therefore let ourselves

1:24:34

off the hook . I don't know what the mythological

1:24:37

underpinnings of this are , but throughout

1:24:39

history there's this tendency of human

1:24:41

beings to create false idols , to

1:24:43

mold something in our own image and then say

1:24:45

that we've got godlike powers because we did

1:24:47

that end . Quote . Nolan's comments are

1:24:49

part of an interview about Oppenheimer , which

1:24:52

is an interesting film to add into this conversation

1:24:54

for obvious reasons . Right , we've already made the allusion

1:24:57

to the similarities with the nuclear

1:25:00

bomb . Similar to AI , nuclear

1:25:02

technology was only partially understood

1:25:04

at the time of its development . It

1:25:06

was really a theory , which

1:25:12

is the central theme of the film Oppenheimer's guilt about creating the most destructive

1:25:14

weapon the world has ever seen , especially when he wasn't sure the

1:25:16

true impact of it . One of the more powerful

1:25:19

moments of Oppenheimer , if you ask me , is

1:25:21

when he speculates with Einstein about

1:25:23

whether or not the nuclear explosion will catch

1:25:25

the Earth's atmosphere on fire . In

1:25:28

a lot of ways , it feels like we are currently in

1:25:30

this moment with artificial intelligence . We

1:25:32

are clearly on the precipice of a major

1:25:35

shift and we don't quite know where it's going

1:25:37

. And though we have tons of literary

1:25:39

and cinematic speculation dating back hundreds

1:25:41

of years , all we know for sure

1:25:43

is that a lot of these science fiction films

1:25:46

that explore artificial intelligence will

1:25:48

no longer be science fiction soon , and

1:25:50

, similar to the plot of Terminator 2 , in

1:25:53

a lot of ways they may have inspired the future

1:25:55

that we will soon come to know , because

1:25:57

in Terminator 2 , they reverse , engineer

1:26:00

the hand and then create the thing itself

1:26:02

.

1:26:02

Yeah , self-fulfilling prophecy , until

1:26:05

you get to the later Terminator films , and then

1:26:07

the timeline gets all wonky .

1:26:09

And that is what I have to say about artificial

1:26:11

intelligence and horror . Bye . Bye

1:26:15

.