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The A.I. Revolt Is Here | The Ezra Klein Show

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The A.I. Revolt Is Here | The Ezra Klein Show

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2270 segments

0:00

What is big, ugly, and has united

0:03

Republicans and Democrats at a time when

0:04

it has felt like nothing else could? AI

0:07

data centers. Last August, a heat map

0:10

news poll found that about 4 in 10

0:12

voters would oppose a data center being

0:14

built where they live. By May of this

0:17

year, opposition grew to 7 in 10.

0:19

Florida Governor Ronda Santis, a

0:21

Republican of course, has proposed a new

0:24

citizens bill of rights for AI. The

0:26

incentives [music] of big tech are not

0:28

the same as what's in the interest of

0:31

the people and the public.

0:33

>> Senator Bernie Sanders called for a

0:35

national data center moratorum.

0:36

>> This moratorum will give democracy a

0:39

[music] chance to catch up with the

0:41

transformative changes that we are

0:43

witnessing and make sure that the

0:46

benefits of [music] these technologies

0:48

work for all of us, not just the

0:52

wealthiest [music] people on earth.

0:54

There are over a hundred local or

0:56

statewide moratorium proposals across

0:58

the country. And here in New York,

1:00

Governor Kathy Hokll, not usually

1:02

thought of as a hardcore populist, just

1:04

imposed a one-year moratorum on [music]

1:06

data center construction.

1:07

>> These hypers scale AI data centers

1:09

consume enormous amounts of power. Truly

1:13

threatening to outpace our grid's

1:16

capacity

1:17

and they drive up costs for local

1:19

rateayers.

1:21

and I refuse to let those costs be

1:24

passed on to New Yorkers who already pay

1:27

too much for their utility bills.

1:29

>> So, I wanted to get into the fight over

1:31

data centers. How much of this is really

1:33

about water or electricity or aesthetics

1:36

and how much is about AI itself and the

1:38

companies that are behind it? My guest

1:41

today is Jasmine [music] Sun. Jasmine

1:43

has been doing excellent coverage of

1:45

both the culture inside the AI

1:46

companies, [music] unusual culture, and

1:48

the anger that is building against them

1:50

in the rest of the country. I highly

1:52

recommend following her Substack, but

1:54

right now she just finished a reporting

1:55

trip in the Midwest talking to the

1:58

people organizing against these data

2:00

centers and I wanted to hear what she'd

2:02

learned.

2:08

>> Jasmine Sun, welcome to the show.

2:10

>> I'm so excited to be here. So, you just

2:12

got back from a reporting trip in

2:14

Wisconsin and Michigan covering the

2:16

fight over data centers. Let's just

2:19

start with what you see when you're near

2:21

a data center. What does it look like?

2:24

>> I think one of the most important things

2:26

about rural Wisconsin and rural Michigan

2:28

is how beautiful it is. Um, I felt like

2:31

I was in Eden. I felt like I was in

2:33

paradise. It's incredibly lush,

2:35

incredibly green. And as you get closer

2:37

to a data center, you start to see more

2:40

power lines. You start to see more

2:42

towers. And eventually you just see what

2:44

looks like an extremely

2:47

large flat warehouse, but you just see

2:50

this sort of like verdant landscape give

2:53

way to what is a windowless industrial

2:56

park. Data centers are very ugly. Um, I

2:59

think I didn't appreciate this until I

3:01

started standing in front of them,

3:02

getting near them, listening to them.

3:04

People will time how long it takes to

3:07

drive past a data center on the highway

3:10

going 70 miles per hour in Port

3:11

Washington. I think it's like a minute

3:13

and 42 seconds. The size of these

3:15

things,

3:16

>> that's a long on a highway.

3:17

>> It is a long, long ride. Like these

3:19

hypers scale data centers are huge. They

3:22

are massive. And so I think that the

3:24

aesthetic questions right around is this

3:27

what I want my state, my community to

3:29

look like, these are really salient to

3:31

people. You mentioned hearing them. Yes.

3:34

What do they sound like?

3:36

>> Oh my gosh. I mean, they sound like

3:38

humming, buzzing, warring. Every once in

3:42

a while, you'll hear a rattling.

3:43

>> Residents who live next door to some of

3:45

them say they're producing noise that's

3:47

not only annoying, but debilitating,

3:49

like this right here.

3:55

>> But again, they're windowless. There are

3:57

not that many workers inside. Um, so

4:00

they're very mechanical sounds. They are

4:02

inhuman as a lot of folks would say.

4:04

>> So you spent a lot of time with people

4:06

organizing against data centers. Uh who

4:08

were they?

4:09

>> Um you had stay-at-home moms, you had

4:13

retired executives, you had um farmers

4:17

who didn't like the impacts on their

4:19

land. Uh you had activists, professional

4:22

activists with environmental groups in

4:24

the state. Um, it was an interesting mix

4:26

of people, but a lot of women relatively

4:30

more left-leaning, though definitely

4:31

some right-leaning folks as well.

4:33

>> So, one question I've heard people ask

4:35

is, how much is this different than

4:37

other kinds of industrial installations?

4:42

I mean, there are a lot of things that

4:44

are built all over the country that you

4:46

wouldn't necessarily want to be right

4:48

next to. Are data centers unusual in

4:50

this or are they, you know, from

4:53

fracking to industrial agriculture just

4:56

like the latest version of it?

4:58

>> It's a good question. It's one I had and

5:01

thought a lot about before I went. Um,

5:03

and I've talked to city officials who

5:05

are confused by this question of we had

5:07

a chip fab here, we had an auto plant

5:09

here, we had a fulfillment center here,

5:10

and nobody cared as much. Why are data

5:13

centers so much more unpopular than say

5:15

solar farms which also faced local

5:17

opposition in places like Michigan? And

5:19

so I think while the quality of life

5:22

concerns around this thing is loud and

5:25

annoying and ugly and consumes resources

5:26

are very similar to other industrial

5:28

projects um there must be some reason

5:32

that opposition is so much more severe

5:34

and widespread even beyond the

5:36

communities where the data centers are

5:38

literally being built. And I think that

5:40

question has a lot to do with the AI

5:42

with the AI industry and sort of the way

5:44

that people feel about these companies

5:46

and these projects.

5:48

>> When I read your reporting on this, when

5:50

I've talked to people involved in this,

5:51

it always feels to me there are sort of

5:53

three layers of concerns that are

5:55

converging

5:56

>> into what we call the data center

5:57

backlash. There's process,

6:00

>> then there's direct impacts,

6:02

you know, the environment, water,

6:05

electricity,

6:06

>> and then there's AI itself. And maybe

6:09

let's go through them sort of one by

6:11

one. One thing that I have been hearing

6:14

a lot of and and I've seen in your

6:16

reporting as well

6:17

>> is the anger over how these processes

6:20

are going and in particular the use of

6:22

NDAs which is not that common. Right.

6:24

I've covered a lot of

6:25

>> what does it take to build a housing

6:27

development and you don't tend to hear a

6:28

lot of the city councilmen got put under

6:31

an NDA,

6:32

>> right?

6:32

>> So what is happening with these NDAs?

6:35

Yeah, I mean this is also something that

6:36

really surprised me and um I think the

6:39

NDAs that I

6:40

>> should say non-disclosure agreements,

6:41

>> right? The non-disclosure agreements,

6:43

this has really inflamed the amount of

6:45

local opposition that you see. And so

6:47

basically what would happen oftentimes

6:49

is there would be some sense starting in

6:51

city council that maybe a big

6:53

development project was going to show up

6:55

but because of the NDAs the council

6:57

members would not be able to disclose um

7:00

that necessarily it was a data center

7:02

necessarily who the customers were going

7:04

to be a company like OpenAI or a company

7:06

like Anthropic or whoever um or even the

7:09

size of the project like how much

7:10

electricity is this actually going to

7:12

consume but whispers would start to get

7:14

around. I was talking to um a VP of a

7:17

construction union and he was saying,

7:19

you know, there's an old Irish saying

7:20

that the only way to keep a secret

7:21

between three people is to kill two of

7:23

them, which I thought was hilarious. And

7:24

so he's saying when these developers

7:26

show up, they talk to the general

7:27

contractor. The general contractor talks

7:29

to all their subcontractors, the

7:30

subcontractors talk to all their

7:32

workers. Yes, maybe everyone is signing

7:34

NDAs at every part of that process, but

7:36

whispers get around. And as soon as

7:38

whisperers get around, you start to get

7:40

social media posts. You start to get

7:42

rumors and the city council because they

7:44

are beholden to these NDAs, they lose

7:46

the ability to get ahead of the social

7:48

media narrative. That was something I

7:49

repeatedly heard from these local

7:50

government officials was we could not

7:52

get ahead of social media because we had

7:54

signed an NDA and rumors started getting

7:56

around.

7:56

>> But why do the companies want these NDAs

7:58

signed?

7:59

>> I mean, I think they didn't think about

8:01

it. They didn't realize there would be a

8:03

backlash. They just thought it would be

8:04

easier in case they change their mind.

8:07

These companies sign lots of NDAs with

8:08

their own workers, with anyone who works

8:10

with them. I don't think there's a good

8:12

reason. Microsoft has actually decided

8:14

to stop using NDAs because of the level

8:16

of backlash. I've heard from uh people

8:18

managing compute at some of the other AI

8:20

labs that they are thinking of making

8:22

the same decision. One thing that

8:24

surprised me is all of the pro data

8:26

center, probuild people who I spoke to,

8:28

whether workers or AI developers, they

8:31

all regret the NDAs. They all think that

8:33

they made the situation much worse.

8:35

>> What is the impact of a new data center

8:38

on water usage, water availability in a

8:41

town?

8:42

>> They do require some of it obviously

8:45

primarily for cooling the data centers

8:47

because these chips and servers run

8:49

really hot and they need AC. Um the

8:51

thing that's gone a bit wrong in the

8:53

water debate I think is that today's new

8:56

data centers are almost all closed loop

8:58

systems. closed loop in the same way

8:59

that air conditioning is closed loop

9:00

which means they're recycling the water

9:02

within the system and they use a

9:04

fraction of the water that you know golf

9:06

courses use and in fact in places like

9:08

Jainsville Wisconsin we would often see

9:10

a literal golf course right next to the

9:12

data center site but they do use some

9:13

and it has sort of become uh a very

9:17

sticky icon of like these things

9:19

resource consumption a lot of folks I

9:21

talked to in Wisconsin and Michigan they

9:22

would say things like you know they're

9:24

building right by the great lakes why

9:26

would they do that if they weren't

9:27

trying to drain the lakes Why would they

9:28

do that if they didn't need all this

9:29

fresh water?

9:30

>> And so your your view is at this point

9:32

the technology has changed such that

9:33

water is not as big of a deal as maybe

9:36

it actually was a couple of years ago.

9:39

>> I think the next thing people have heard

9:41

a lot about is energy usage.

9:43

>> So walk me through that.

9:44

>> Uh the electricity consumption issue is

9:46

real. So um data centers do in fact use

9:49

an incredible amount of electricity. Um

9:51

these uh these chips and these servers

9:54

that are processing gigantic

9:56

mathematical calculations to make AI

9:58

work require tons of energy. All these

10:01

chips and clusters are talking to each

10:03

other. You need the interconnections to

10:04

be really fast in order to get like a

10:06

chatbt answer really quickly with low

10:09

latency. You need these super fast

10:11

connections. All of that's powered by

10:12

electricity. So we are talking about a

10:15

really really significant amount of new

10:17

electricity that is going to require new

10:19

generators, new power plants. It's

10:20

probably going to be natural gas in the

10:22

near future. Once the data center is

10:23

fully operational, there is not a ton of

10:26

air and water pollution, assuming that

10:28

everything's working correctly. They are

10:29

relatively clean facilities, but you

10:32

know, like a lot of folks are concerned

10:34

about the electricity use. They're

10:35

saying, "Yeah, maybe the data center

10:37

doesn't use that much water. Maybe the

10:38

data center doesn't pollute that much,

10:40

but what about all of these, you know,

10:42

new power plants that they're going to

10:43

build in order to power it?" When the

10:46

tech companies come into these towns and

10:47

begin talking to the city council

10:49

members, when they begin talking to the

10:50

community, what are they sort of

10:53

promising on the one hand, right? This

10:55

this is why this will be good for you.

10:57

And what are they asking for on the

11:00

other?

11:01

>> Yeah. I mean, so these things do provide

11:02

an incredible amount of tax revenue,

11:04

right? And so, um, in Mount Pleasant,

11:06

the on the old Foxcon site, which ended

11:09

up being bought out by Microsoft, they

11:11

saw, oh, there's all this infrastructure

11:12

already here. Why don't we build a

11:13

hypers scale data center on this unused

11:15

industrially zoned land? Uh Microsoft is

11:17

on track to pay $19.6 million in

11:20

property taxes in 2026. This is expected

11:23

to continue for many years. Again, this

11:25

is a small village of 28,000 people. Um,

11:28

and so there are really meaningful

11:30

property tax benefits. And I do think it

11:33

I find it frustrating personally when

11:35

anti-data center organizers say that the

11:37

job creation is a myth because I think

11:38

that 500, you know, maybe six figure

11:41

jobs for folks who go through

11:43

apprenticeships, but maybe don't need

11:44

college degrees that last two to six

11:46

years. That's enough time to build a

11:48

family. That's enough time to buy a

11:49

home. I think it's super meaningful. And

11:50

when I talk to technicians, when I talk

11:52

to workers, clearly it was extremely

11:54

meaningful work. Um, I think what one of

11:57

the things that was the most surprising

11:58

to me when I talked to data center

12:00

activists was that they they responded

12:03

to so many of the proarguments with I

12:07

don't believe them. So like this company

12:10

says that they are going to treat the

12:13

water with chemicals in it so that it

12:15

doesn't flow into the lakes. People

12:16

would say I don't believe them. I don't

12:18

think they can do it. people would say

12:20

uh the companies would say we are going

12:22

to cover uh the cost of our own

12:25

electricity grid buildout. We are going

12:27

to ensure that rates do not go up for

12:29

all Michiganders. Um a lot of folks

12:31

would say I don't believe them. DTE has

12:34

raised our electricity rates basically

12:35

every year since 2022. Why would this be

12:38

the year that they decide not to do it?

12:40

I do not believe them. They are going

12:42

the we are going to create 500 jobs and

12:45

some of these will stick around after

12:46

the data center is built. people just

12:48

said I don't believe them. It was really

12:50

clear to me that data centers are

12:52

showing up in an environment of

12:53

extremely low trust in both governments

12:55

and in corporations to the extent where

12:58

the proarguments almost do not land

13:00

because people just aren't interested in

13:03

anything an outside tech company is

13:04

going to tell them. They say they have

13:06

big PR teams. They can say whatever they

13:07

want. One thing that became really

13:09

obvious to me when I talked to both

13:10

people at the AI companies and local

13:12

officials is that two years ago, no one

13:14

thought that data center backlash was

13:15

going to be like this. And so these

13:17

companies were in fact looking for

13:19

things like um does this state have a

13:22

sales tax exemption as Wisconsin does to

13:25

ensure that they don't have to pay sales

13:26

taxes on their very expensive chips on

13:28

their very expensive GPUs. Um they were

13:30

often looking to build in places that

13:33

might even offer local subsidies to the

13:35

companies for building in that area. I

13:38

think that a lot of the balance of power

13:40

has shifted as local opposition has

13:42

ramped up. Um, now it's the case that

13:45

I'm hearing from some local officials if

13:47

we did this again today, we wouldn't

13:49

have to offer any subsidies because in

13:52

fact now there is so much local

13:54

opposition that the developers are

13:56

really looking where is there going to

13:57

be a comm a local community and a

13:59

government that is friendly to our

14:01

project. How can we, you know, have a

14:04

Christmas tree ornaments worth of

14:06

community benefits agreements? And so

14:08

just the nature of these deals and how

14:10

much they are skewed towards communities

14:12

versus the AI developers has really

14:14

changed. One of the things that came up

14:16

a lot in your reporting and that I

14:18

thought was interesting was the fear

14:20

that this is a bubble

14:21

>> for sure.

14:21

>> And what's going to happen is your

14:23

community will agree to something and

14:25

then in the middle the bubble is going

14:27

to pop and you're going to end up with a

14:30

halffinish data center or one that is

14:33

not being kept up correctly or something

14:36

where the

14:37

>> you know promised benefits don't emerge.

14:39

I mean you were in Wisconsin which had a

14:41

very very bad experience with Foxcon

14:43

which seems to be structuring the way

14:45

people are thinking about at least some

14:46

of this.

14:47

>> So talk to me a bit about that uh set of

14:50

concerns.

14:51

>> Absolutely. Yeah. I think in terms of

14:54

what people in these communities with

14:56

these data centers feel when they see

14:57

the projects come in with their gigantic

15:00

like $2 billion of investment like these

15:02

gigantic numbers that are being dangled.

15:04

It feels like a bubble to them. One,

15:06

they're seeing news articles saying

15:07

maybe a AI is a bubble. We don't know

15:09

it's a bubble, but it could be. Two, you

15:11

do have exper experiences like Fox Con

15:14

where you have an big tech company show

15:17

up in a very small community, in this

15:18

case, Mount Pleasant, Wisconsin, a city

15:20

of like 28,000 people. It's not very

15:22

big. Get, you know, hundreds of millions

15:25

of dollars in infrastructure investment

15:26

and tax subsidy from the from the town.

15:28

Promise 13,000 highpaying manufacturing

15:31

jobs and then pull out because the

15:33

contract wasn't set up correctly. they

15:35

decided they didn't actually want to

15:36

build a bunch of flat screen TVs in

15:37

Wisconsin and the you know the town is

15:40

left on the hook having invested all of

15:42

this money in the grid and in roads they

15:44

got I think a thousand jobs in the end

15:46

Foxcon is still paying back all of this

15:48

debt that has been accumulated and so

15:51

experiences like that have really really

15:53

soured people on the question of when an

15:54

outside big tech company comes in and

15:56

you know promises these gigantic numbers

15:59

and all of these jobs and all this tax

16:01

revenue and it's for this technology

16:02

that like you can't a lot of people they

16:04

don't see, they don't feel, they don't

16:05

find personally extremely extremely

16:07

useful, not at the levels of these

16:08

valuations. They have a lot of questions

16:10

about if the bubble pops, are we going

16:12

to be the ones left with a stranded

16:14

asset in our community? I mean, in

16:15

Jainsville, Wisconsin, um it was

16:17

famously the site of this 100-year-old

16:19

GM plant um that was the centerpiece of

16:22

the community that employed a ton of

16:23

people. when they left during the

16:25

financial crash in 2008 and the plant

16:27

closed down. Not only did it sort of

16:29

devastate the community from a work

16:31

perspective, um but they also left $30

16:35

million of contamination and hazardous

16:37

waste in the middle of the city that has

16:39

never been cleaned up. There's forever

16:41

chemicals in there. This is why

16:42

developers have not been able to sell

16:44

this brownfield is because there's so

16:46

much waste that GM never cleaned up. And

16:49

so I think that people worry about what

16:51

happens if the AI bubble pops. If maybe

16:54

it doesn't pop and the data center

16:56

developers just decide, never mind, we

16:58

want to build elsewhere. Never mind,

16:59

this data center isn't good enough. We

17:01

have newer, better technology. And who's

17:03

going to be left holding the bag? That

17:04

was the question I heard over and over

17:05

again.

17:06

>> But this is something that I do think is

17:07

in people's minds, right? You you bring

17:09

this in and right now you're at this

17:11

time of very very high valuations,

17:12

>> right? And if AI demand isn't quite what

17:15

you think or even just the company that

17:16

was behind this particular data center

17:19

is not part of the winner's circle

17:22

>> that in a couple years what you got is

17:24

this like giant

17:25

>> box.

17:26

>> Yeah.

17:27

>> That's not going to continue being

17:29

valuable. And so whatever the promised

17:32

benefits are from it, you know, tax

17:33

revenue, etc. Yeah. Maybe they show up

17:35

for a while.

17:36

>> Yeah.

17:37

>> But then what if in 5 years they're

17:38

gone, but you are left with this

17:40

infrastructure. It's like they can leave

17:42

Jainsville, right,

17:43

>> with no real concern. They're not there.

17:45

Their people don't live there, right?

17:46

But if you're in Jainsville, you do live

17:48

there.

17:48

>> Yes.

17:49

>> Yeah. A real concern.

17:51

>> You see the You see things like this

17:52

with Elon's giant Colossus data centers,

17:54

right, that he built out in Memphis?

17:56

>> And what makes people feel better about

17:57

a new construction project in their town

17:59

than calling it Colossus?

18:01

>> Oh, yeah. [laughter]

18:03

Yeah. I mean, these things

18:04

>> unairring touch for the people.

18:06

[laughter]

18:07

I mean, so usually the thing that

18:08

happens is they give them very cutesy

18:09

names like Project Canoli and the barn

18:12

and they try to make them sound as

18:13

friendly as possible. But yeah, I mean

18:15

with Colossus, XAI never really took

18:17

off. People were not in fact using Grock

18:19

as much as Elon thought he they were

18:21

going to be using it. And in that case,

18:23

he was able to get a really good deal

18:25

selling the compute capacity to

18:27

Anthropic, which was growing like crazy

18:28

and had not built enough data centers on

18:30

their side. But you could totally

18:32

imagine a world as you say where in fact

18:35

you know XAI decides we are going to

18:38

focus on space. We don't care about AI

18:40

anymore. Maybe there's non-anthropic to

18:42

pick up the bill because anthropic has

18:44

maybe built enough of their own compute

18:45

capacity. There is an open question

18:47

about what happens in that world. So uh

18:49

I wrote abundance uh last year with

18:51

Derek Thompson who published it

18:53

>> and one thing I've heard been asked by a

18:56

lot of people is like what is the

18:56

abundance take on a data center

18:59

>> and the like the beginning of that book

19:02

has this line that uh you know the

19:05

question is what do we need more of and

19:06

how do we get it

19:08

>> and I think the question here that has

19:12

been so [snorts] hard for the AI

19:14

companies for the people trying to build

19:15

data centers is

19:19

actually getting people to believe they

19:22

need more of them. Right? When you're

19:23

talking about building affordable

19:24

housing, when you're talking about, you

19:26

know, building an array of solar panels

19:28

or wind turbines,

19:31

>> there's a pretty legible argument.

19:33

>> Yes.

19:34

>> For why you need that, right? People

19:35

still may not like it, but we need homes

19:38

because we need places for people to

19:40

live.

19:41

>> We need solar panels because we need

19:43

clean, renewable energy.

19:45

How much is this like a normal kind of I

19:48

don't even exactly want to call it

19:49

nimism but uh but a normal kind of I

19:53

don't want the industrial infrastructure

19:55

built in my backyard because like you

19:58

know what am I going to get out of that

20:00

>> and how much of it is actually something

20:01

that is more related to people's

20:04

feelings about AI which is I don't want

20:07

this built here because why would I want

20:10

to pay the cost for a thing that I don't

20:12

want there to even be more of in the

20:14

first device.

20:16

>> This I think was one of my big

20:17

motivating questions going into this

20:19

trip is is it quote unquote normal

20:21

nimiism? Is it about AI? Is it about

20:24

something else? And so I spent time both

20:27

looking at polls and trying to talk to

20:28

people about would you be excited if

20:30

this was a chip factory which would use

20:32

a lot more water and pollute a lot more.

20:35

Would you be excited if it was a solar

20:36

farm? Also maybe acquiring agricultural

20:39

land and turning it into industrial use.

20:40

Would you be excited if it was a million

20:42

other things? And um I talked to Nick

20:44

Bagley who you've had on your show about

20:46

is this just proceduralism and we talked

20:50

about the solar farms example where

20:51

solar farms uh the opposition use very

20:54

similar tactics to the data center

20:56

opposition. They were organizing in

20:57

Facebook groups. They were packing town

20:59

halls. They were talking about the local

21:01

impacts and the importance of farmland

21:03

and the visions for their communities.

21:05

Um there were zoning fights of course.

21:07

Um, but like you say with the solar

21:10

farms, you do have a very clear procase.

21:13

You have a faction. You have a group of

21:15

people, a constituency, people who care

21:17

about the environment, who want

21:18

renewable energy, who understand that

21:20

that's a thing that, yeah, maybe it

21:22

sucks to have in your backyard, but you

21:23

can take one for the team because this

21:24

is important for our planet. Um, you

21:27

don't really have a pro- faction with

21:28

AI. Same with like the auto plant,

21:30

right? You have one, you have maybe

21:32

7,000 workers in the old GM plant in

21:34

Jainsville who all have families who

21:37

really care about them, who see that as

21:38

a constituency. Everyone drives a car.

21:40

They see their car as essential. I think

21:42

the fact that it's creating these

21:43

tangible outputs really, really matter.

21:45

Um, I don't think that data centers have

21:49

a compelling

21:51

proconstituency besides the utility

21:53

companies and the AI companies which are

21:55

already incredibly incredibly unpopular.

21:58

And I went in and asked these

21:59

organizers, do you guys use AI? I do

22:02

find it useful. This was one of the top

22:03

questions that my friends in San

22:04

Francisco wanted me to ask is, "Are

22:06

these people like using Chat GBT?" And

22:08

they don't even realize that the data

22:09

centers are how they can use it. And

22:11

what I found there was a lot of these

22:14

folks did say, "Yeah, I've used it to

22:16

draft an email or make a meme." They're

22:18

not denying that AI might have any

22:20

possible utility at all. Um, but they

22:23

clearly didn't see it as essential in

22:25

the way that cars, energy, and housing

22:27

are essential. They clearly saw it as

22:29

kind of like a widget, a toy. Um, and

22:32

maybe there are these risks, maybe

22:34

there's the job stuff, but fundamentally

22:35

they were like, "This thing is not that

22:37

useful. I don't really see in my

22:38

personal life how this could justify

22:40

these gigantic valuations." And so I was

22:43

talking to for example um Charles

22:44

Franklin who runs Marquette Law Polls in

22:46

Wisconsin and he was explaining that

22:48

usually you see 50/50 polling on issues

22:50

where you have a strong anti-case and a

22:52

strong proase and the only reason you're

22:54

kind of seeing this 7030 bipartisan

22:56

opposition to data centers no matter

22:57

whether you live near a data center or

22:59

you don't which means it's not just

23:00

nimism it's you don't want a data center

23:01

in anyone's backyard um is because he

23:04

was like there is no strong proargument

23:06

for it. There is not even a fight that's

23:09

really going on. Nobody wants it was a

23:10

phrase I heard over and over.

23:12

>> You have a very influential definition

23:14

of AI populism where you call it a

23:16

worldview in which AI is viewed not only

23:19

as a normal technology but as an elite

23:22

political project to be resisted.

23:25

Unpack that for me.

23:27

>> The phrase that you hear a lot from AI

23:29

critics is why is this being shoved down

23:31

our throats? um or with you know chatbt

23:35

it's not that people are saying there is

23:38

literally no use for chatbt it's people

23:40

are saying why are you forcing me at my

23:42

job to use AI to do something worse when

23:45

I could do it better and so I think that

23:48

a lot of the public backlash to AI that

23:51

has risen over the past six months is

23:53

not explained by people thinking that

23:56

the technology has no use at all um it's

23:58

not explained by them being worried

24:00

about specific technical property

24:02

properties of LLMs that might lead to

24:04

rogue AI or misalignment or whatever,

24:05

which are the sort of safetiest

24:07

arguments. It's AI as sort of an avatar

24:09

for a small group of Silicon Valley

24:12

billionaires ability to impose their

24:15

vision of the world onto everybody else

24:18

without their consent. And I think

24:20

that's also what I hear echoed in these

24:22

data center debates. It's not just uh

24:25

it's going to use this much water or

24:26

that much water. I frankly think that

24:28

even if there was no misinformation

24:30

about water use, people would be just as

24:32

angry about the data centers.

24:33

>> Yeah. I consider the water I don't want

24:34

to say the water issue is fake. Um what

24:37

I will say is like there was a debate

24:39

>> Yeah.

24:39

>> uh online a while back about how much um

24:43

water like a chachbd query

24:45

>> Yeah.

24:45

>> consumed. And somebody was like if you

24:48

really care about water are you are you

24:49

eating beef?

24:50

>> Yes. As someone who doesn't eat meat, I

24:53

thought this was a quite good like you

24:55

could really save a lot of water by

24:56

going vegetarian.

24:57

>> Yes.

24:58

>> Um and relatively much much more than

25:00

not using cha and relatively few people

25:02

in that conversation were giving up meat

25:05

>> or giving up YouTube videos

25:07

like use more water than a chachi query.

25:09

>> Which is to say that I think sometimes

25:11

people don't like a thing and they're

25:13

looking for reasons to justify that

25:15

dislike.

25:16

>> Yeah.

25:16

>> But what's actually happening at the

25:18

base is they don't like the thing.

25:20

>> Right. and the data centers like as

25:22

you're saying I think speak to this AI

25:25

populism question like even more

25:27

precisely because the issue with AI

25:29

itself is that I think people's

25:32

relationship to it is very complicated

25:34

right I have myself a very complicated

25:37

relationship to AI like I use it a fair

25:39

amount

25:40

>> I'm not sure I think it's a good thing

25:41

for society the way it is going I don't

25:44

want my kids using it I know they'll be

25:45

using it like maybe it'll make things

25:48

better but I really don't know like I

25:49

think that the costs are going to be

25:50

very very high for us relationally and

25:52

economically and you know and so I just

25:55

I'm very conflicted

25:58

>> but do I want to live next to a data

26:00

center? Yeah. No.

26:01

>> Yeah. [laughter] It's totally different.

26:02

>> Like that's easier.

26:03

>> I mean one of the most

26:04

>> somebody is just making you do that.

26:06

>> Yes. of like going to this um I back

26:08

toback I went to this Abdul Bernie AOC

26:10

rally in Lancing, Michigan and then I

26:12

went and saw the Seline activist the

26:14

next day and I was researching how the

26:15

Seline Stargate project happened and it

26:17

was really interesting to see these

26:18

echoes of the populist message sort of

26:21

manifest in this specific project. Like

26:23

when I'm at this rally, people are

26:25

talking about the oligarchy. talking

26:26

about uh corporate billionaires, whether

26:28

it's big tech or big pharma or DT, the

26:30

utility companies, um paying off

26:33

politicians in order to, you know, screw

26:36

the people over. And that's why you need

26:38

the people to come together and to get

26:41

money out of politics to prevent DT from

26:44

donating to these super PACs and paying

26:47

off Gretchen Whitmer or whatever. And um

26:50

then when I learned how the Selen data

26:52

center saga played out, what happened

26:53

was the Selen Township City Council,

26:55

unlike a lot of city councils actually

26:57

voted 41 against reszoning their land

26:59

for the data center. So this was a case

27:01

where local government said, "This is

27:03

not our vision for our community. It's

27:04

not worth it to us." And what happened?

27:06

The data center developers sued Selene

27:09

Township, a town of like again a few

27:12

thousand people, um into saying, "Wait,

27:15

no, this is exclusionary zoning. you

27:17

can't have no industrial use in your

27:19

entire township. And when a town of that

27:21

size is getting sued by a giant AI data

27:24

center developer, they just settled.

27:25

They were just like, fine, give us a few

27:27

million for the fire department and for

27:28

some schools. And this fight is not

27:30

worth it to us. But that to people felt

27:32

like a profound a profound violation of

27:34

little democracy. It felt like the dark

27:36

money and politics story, which is, you

27:38

know, you have some very rich companies

27:41

show up with the bag of money to your

27:43

politicians. They don't tell anybody

27:44

else what's happening. the politicians

27:46

aren't allowed to tell their citizens

27:47

and involve them in the decision-making

27:49

process and they themselves work out a

27:51

deal, a deal that is fundamentally

27:53

asymmetric because of the amount of

27:54

money on one side that will then

27:56

transform the image of your community,

27:58

your lived reality into the world that

28:00

these tech companies have decided for

28:02

you. And so I think that the data

28:04

centers in that sense are a very

28:05

visceral uh microcosm of the way that a

28:08

lot of people feel that AI is showing up

28:10

in their lives. I

28:10

>> I would also maybe even take that a

28:12

little bit further. I think that the way

28:15

that not all of the egg companies and I

28:17

think Anthropic has largely been a a

28:20

good actor here, but many of them have

28:22

acted has opened up such a chasm between

28:26

what they say and then how they act

28:29

under pressure that one should be

28:32

incredibly incredibly skeptical of them.

28:33

And what I mean by this is that,

28:36

you know, Sam Alolman and all these

28:38

different people, you know, in front of

28:39

congressional testimony and in

28:41

interviews will say, you know, it should

28:44

not just be us making these decisions.

28:46

There should be a real deep small D

28:49

democratic role here in how AI rolls out

28:53

in um, you know, what effects it has on

28:56

communities and how it is governed.

28:59

And then when a community or a

29:03

politician

29:05

you know who is representing a community

29:08

tries to say well we don't want the

29:10

status here or we want to impose these

29:12

regulations.

29:13

>> We have watched repeatedly these

29:15

companies

29:16

>> turn tremendous amounts of financial

29:18

artillery.

29:19

>> Yes.

29:20

>> Against whoever is standing in their

29:21

way. Right. and to to use this the

29:25

expertise and the money and the power

29:27

they are amassing to kind of

29:29

shortcircuit that democratic voice.

29:31

>> Yeah. I mean a couple things. One is

29:32

like I think one big gap I noticed

29:35

between Silicon Valley and the folks in

29:36

these communities I was talking to is

29:38

Silicon Valley does tend to think that

29:40

money solves all problems. That if you

29:41

just make the check bigger everything's

29:43

going to be okay. And I think people

29:45

have a sense for I'm being bribed. This

29:48

corporation is not offering me a free

29:50

lunch or whatever. there's going to be

29:52

something that I'm losing here. And in

29:54

fact, sometimes the fact that the data

29:55

center deals were bigger or the amount

29:56

of political spending was bigger.

29:58

Actually, it just makes people more

29:59

suspicious. Like in the Abdul race, like

30:01

his number one like hit on Haley Stevens

30:04

is how much money she is getting from

30:06

Apac, from DTE, from Pharma, whatever.

30:09

And so, one is just that I think we're

30:10

in a political environment where making

30:12

the numbers bigger and the amounts of

30:13

money bigger makes people more

30:14

suspicious, not less. Another one I'll

30:16

just quickly mention is I don't even

30:18

think anthropic should be left off the

30:19

hook for things like labor market

30:20

impacts, right? They are the ones

30:22

simultaneously warning that we might see

30:25

a you know 50% of white collar jobs lost

30:27

by 2030. This is really important to us.

30:30

We're freaking out about it. Uh Daario

30:32

has written in his essays um we might

30:34

see an underclass of people of lower

30:36

intellectual ability and they are

30:38

building the agents. They are building

30:40

the coding agents, the banking agents,

30:42

the design agents that they know are

30:45

going to displace jobs or they believe

30:46

at least are going to displace jobs. And

30:48

I think that people feel that hypocrisy

30:50

as well, which is if you are so worried

30:52

about the inequality, why are you

30:53

building the agents to do it? And when I

30:56

ask executives and researchers and

30:57

whoever at anthropic this question, they

31:00

don't really have a good answer because

31:01

it is true that their business model is

31:03

fundamentally premised on the disruption

31:05

that they say they are causing. You did

31:07

a big piece for the Times on the very

31:10

widespread belief in Silicon Valley that

31:13

they will create this underclass.

31:14

>> Yeah.

31:15

>> What does the underclass mean to them?

31:17

>> The idea of a permanent underclass

31:19

caused by AI is basically a world where

31:23

any job a person can do either AI or a

31:26

robot can do for them. which means that

31:28

workers lose all the economic leverage

31:30

they have and capital owners, people

31:32

with money, can simply pay machine labor

31:34

to do all the work instead of paying

31:36

workers. What that means is anyone who

31:38

earned their living by working is no

31:41

longer able to do that. You end up with

31:42

a world of runaway inequality where the

31:44

rich get richer and the working class

31:47

gets poor. Maybe they get some welfare

31:49

checks, but fundamentally it's a loss of

31:51

economic mobility in a society. And when

31:54

I ask folks in Silicon Valley, do you

31:56

think by default AI is going to increase

31:57

or decrease inequality? I have not yet

32:00

heard anyone say it will decrease

32:01

inequality or keep it the same. They

32:03

might say the floor will get really

32:04

high. They might say AI will bring the

32:06

cost of consumer goods down and so

32:08

people's lives are going to get cheaper

32:10

and you know everyone will be super

32:11

healthy so it's okay. But I have not

32:13

heard a single person in the tech

32:14

industry tell me that they believe that

32:16

AI is going to decrease inequality. And

32:19

in fact, many people are very worried

32:20

that instead most workers will lose

32:23

their leverage and be on a kind of

32:25

permanent welfare in the faroff future.

32:27

>> I I'm pretty skeptical of this vision,

32:30

although I don't rule it out, right? It

32:32

might happen. Although, I just don't

32:34

think AI is going to be quite as

32:35

revolutionary as a lot of these people

32:36

think and will not diffuse into the real

32:38

world as easily. But, you know, the

32:41

thing you're going to need to adjust to

32:43

any major technological change is time.

32:46

And then also it's like the AI industry

32:49

is in like an allout war to make sure we

32:51

have as little time for adjustment as

32:52

possible. [laughter]

32:53

>> I mean look at I just find it hard to

32:54

like unnot that

32:55

>> how many enterprise salespeople are open

32:58

AI and anthropic hiring in order to

33:00

convince companies that they can replace

33:02

their workforce or not maybe not replace

33:04

but expand their workforce with agents

33:07

instead of humans. Right? They are

33:09

having these sales conversations trying

33:11

to persuade people of these questions. I

33:13

don't think that a permanent underclass

33:15

is the likeliest outcome economically

33:18

that we're going to get. I think that AI

33:19

is actually just really jagged and human

33:21

jobs are super complex and super hard to

33:23

automate. And most of the folks who are

33:26

predicting economic apocalypse haven't

33:28

actually worked enough real jobs to know

33:30

how complicated and how multiaceted most

33:33

jobs really are. But I definitely agree

33:36

on the speed point. I think that like

33:38

Alex economist has made this point very

33:40

well. Um, one thing I think a lot about

33:41

are people say, well, humans can adjust,

33:44

humans can reskill, they can retrain,

33:45

they can just do the new jobs that we're

33:47

going to develop instead. But you look

33:49

at things like software engineering

33:50

where people will often say now, um,

33:52

senior software engineers are doing

33:54

great. They love cloud code. Um, junior

33:56

software engineers have been mostly

33:58

replaced and you see hiring and job

34:00

postings are down in that sector. Well,

34:02

do we think that a human software

34:05

engineer is going to rescale or upskill

34:08

themselves faster than the next model is

34:10

going to get better at software

34:11

engineering? That's the question that I

34:12

really wonder about is if AI progress

34:15

outpaces humans ability to reskill,

34:17

retrain, upskill, adapt, then I'm not

34:20

really sure what there is going to be

34:22

left there. There will be some jobs

34:24

left, but it's going to be a really

34:26

really painful adjustment. I have had so

34:29

many people at the top of these

34:31

companies, right, the very tippy top,

34:34

tell me they wish all this would slow

34:36

down.

34:37

>> Yeah,

34:38

>> I'm sure you have had them say this to

34:39

you, right? But in this world where

34:43

in their unguarded moments, they will

34:45

say they wish all this was going slower.

34:48

Well, one way to slow AI down is to

34:52

constrict the number of data centers you

34:54

can build.

34:55

>> Yeah.

34:56

just like you've done, you know, as good

34:58

a reporting as anybody on just how

35:01

conflicted people even working for these

35:03

companies seem to be about what they are

35:05

building and yet that yet they're in

35:07

this competitive race to build it as

35:08

quickly as possible.

35:10

>> And so it makes them a pretty

35:11

unconvincing

35:13

>> pro faction.

35:14

>> Oh, absolutely.

35:16

>> We're building the thing we're telling

35:17

you to be afraid of and we need to build

35:19

it as fast as possible even though we

35:21

sort of admit that it would be better if

35:22

the whole thing was slowed down.

35:24

It's very confusing.

35:25

>> It's a weird argument.

35:26

>> Yeah, it's so confusing.

35:28

>> I remember when I sat down with Abdul

35:30

Aliad, the Michigan Senate candidate, he

35:32

cited Dario's 50% white collar job lost

35:35

stat probably like five times in the

35:36

30-minute conversation. It's like he was

35:38

like, they're saying that there's going

35:40

to be recursive self-improvement and it

35:41

might kill us all. Like, yeah, I get why

35:43

you would not want to make this thing go

35:45

faster. This is true for data centers,

35:47

but it's true for any other reason way

35:49

that you might slow AI down, which is

35:51

that everyone only wants to be slowed

35:54

down if they can guarantee that the

35:56

other companies that the Chinese labs

35:57

are going to slow down with them. So

35:59

long as that's not true, they're going

36:01

to keep racing. And I think for that

36:03

reason, yeah, I mean, the thing that I

36:05

hear when I talk to people at the

36:07

companies, data center executives about

36:09

the buildout is how much money do we

36:12

need to give these cities to let us

36:13

build a data center? tell us how to

36:15

bribe them better. Tell us what we can

36:16

do. And so when I talk to them about the

36:18

buildup, I'm not hearing any sort of

36:20

personal moral reckoning with slowing AI

36:23

down. I'm hearing how do I make the

36:24

bribes bigger? How big do they need to

36:26

be?

36:26

>> So then how do you reconcile what

36:30

many of these executives, many of these

36:32

AI company workers are telling you about

36:34

their fears of creating an underclass,

36:36

about their fears of losing control. I

36:37

mean we just saw the situation where uh

36:41

open AI's model was breaking out of a

36:44

sandbox in order to sort of cheat on its

36:46

evaluation right so the AI safety people

36:48

are very worried right the safety teams

36:50

in here clearly don't have full control

36:51

or even understanding of what they're

36:53

building

36:54

>> how do you reconcile if you reconcile

36:58

the way the AI companies talk when they

37:01

are giving voice to their fears or the

37:03

people at them talk when they're giving

37:04

voice to their fears

37:07

and their like pretty profound hostility

37:11

to anything that would slow down how

37:13

fast we are building this thing whose

37:16

consequences they freely admit they

37:19

cannot predict.

37:21

>> Yeah, it's fascinating because just on a

37:22

very personal level when I talk to

37:24

people at these companies I just think

37:26

like man if I thought this thing might

37:27

have a 10% chance of killing us all or

37:29

taking taking everybody's job I wouldn't

37:32

work on it. I would not build that. I

37:34

personally [laughter] could not morally

37:36

justify taking that chance. And and when

37:38

I talk to people who are not in the San

37:41

Francisco AI world, they feel like I do.

37:43

They're just like, why would you do it?

37:44

And I think there are basically three

37:46

rough buckets of rationale that I hear

37:48

from people um or that I hear between

37:52

the lines from people. One is um this

37:55

sort of sense of technetism.

37:58

It's super intelligence is going to be

38:00

built inevitably. there is no way it's

38:02

not going to happen. If it happens, I

38:05

want to be part of it. I want to make my

38:06

money from it. I want to maybe make it

38:08

happen in the least bad way. I think

38:09

that's a super common answer. Another is

38:13

um

38:16

this technology might kill us all, but

38:18

it also might be really amazing. It

38:20

might produce super abundance for

38:22

everybody. We might be immortal.

38:24

um it might double everyone's lifespans,

38:26

cure all diseases, bring the cost of

38:29

every consumer good, housing, energy,

38:31

whatever to near zero. And that would be

38:33

utopia. And so I think all the time to

38:37

that anecdote that I think SPF said on a

38:40

podcast where it's

38:41

>> Sam Bankman Freed.

38:42

>> Yeah, Sam Bankman Freed sent out a

38:43

podcast where it was like if you could

38:44

flip a coin and it was 51% odds you

38:47

would double the total amount of like

38:49

human welfare and 49% chance everyone

38:51

dies, would you flip the coin? He says

38:53

yes. And again, I feel compelled to say

38:55

like caveats here of like, you know, how

38:56

do you really know that's what's

38:57

happening? Blah blah blah, whatever. Put

38:59

that aside. Take the hypothetical, the

39:01

pure hypothetical. Um, uh, yeah. Yeah.

39:05

>> I think this is a hyperbolic example,

39:07

but I think it's not actually that far

39:08

off from what a lot of the people

39:11

building super intelligence believe too,

39:13

that they are basically willing to flip

39:15

the coin. Maybe we all die, but maybe

39:18

we're all immortal, and that expected

39:20

valuewise cancels things out. Um, and

39:22

then the final category is just I think

39:24

folks who are so fascinated by the

39:27

technical endeavor of whether we can

39:28

build this thing and how to do it that

39:30

they just aren't super worried about the

39:32

consequences or what else might happen.

39:34

Um, so people have all sorts of

39:36

self-justifying narratives as to why

39:38

it's worth it. Some I think are better

39:40

than others. Um, but it makes sense to

39:43

me why the public is not particularly

39:46

sympathetic to any of these.

39:47

>> I mean that middle narrative I I heard

39:49

Sam Bankman Freed say that. I think it

39:50

was on Tyler Cowan's podcast and

39:53

>> I was like, "Oh, that's psych that's a

39:54

psychopath,

39:55

>> right?" To actually believe that, you

39:58

would have to be a a psychopath, you

39:59

would have to have a very very very low

40:01

value

40:02

>> on I think human life. Yes.

40:04

>> Right. [snorts] Imagine being the person

40:05

who flips that coin and it comes up

40:07

wrong.

40:07

>> Oh Jesus. Yeah.

40:08

>> Like I'm a parent.

40:10

>> Mhm.

40:11

>> That like the idea that you would do

40:12

something that's like 5149 on like your

40:15

kid is, you know, doubly happy or your

40:18

kid is gone. like you would never you

40:20

you like you don't even want to say that

40:22

out loud.

40:23

>> Of course, I think that's how almost

40:24

everybody thinks about it. And again, I

40:26

think 5149 is obviously the most

40:28

egregious example you could think of.

40:29

And so SBF is very unsympathetic. But

40:32

when I think about the super

40:33

intelligence bet, a lot of people will

40:35

characterize it as a 9010 bet, as an

40:38

8020 bet. And this question of how much

40:40

is an acceptable amount of either

40:42

extinction risk or total disempowerment

40:44

risk. Um, you know, I think people have

40:47

very different risk appetites and

40:49

Silicon Valley is a place that has

40:50

always prized their high risk appetite.

40:53

I think that makes a lot more sense when

40:55

you're talking about maybe yourself or

40:56

your company full of people who have

40:58

opted into taking a very high-risisk

40:59

endeavor. I think that's extremely

41:01

different obviously when you're talking

41:02

about the rest of the world. And one

41:04

thing with the data center debates that

41:05

I'd always hear is like, you know, I get

41:07

that these people are making this crazy

41:09

bet on this technology. They think it's

41:11

going to change the world, but why do

41:12

they have to do it in our backyard? Why

41:14

is Mark Zuckerberg not building a data

41:16

center in his backyard? And so this

41:17

question of yeah, you guys are going to

41:20

create like these very tangible impacts

41:23

and to their view harms on specific

41:26

communities that are not the communities

41:27

benefiting from this technology. At

41:29

least they don't see the benefits yet.

41:30

They don't see the cancer cures. They

41:32

don't see themselves getting these

41:33

million dollar million dollar salaries

41:35

that the AI researchers are getting. It

41:37

feels like I think it feels to a lot of

41:39

these folks like they are pawns in some

41:42

tech billionaires' game and they do not

41:45

like to feel that way.

41:46

>> Why aren't they building it in their own

41:47

backyards? Why don't you see a bunch of

41:48

data centers in, you know,

41:50

>> I mean, I don't

41:50

>> Northern California. [laughter]

41:52

>> I don't think I need to tell you why

41:53

it's so hard to build in Northern

41:55

California.

41:56

>> But I I both I both think that's true

41:58

that it's hard to build in Northern

42:00

California. But I also think there's

42:01

like a truth to the other thing being

42:02

said they don't want them there. No,

42:04

>> I mean the land is expensive. It would

42:06

be very hard like and expensive to build

42:07

a data center like the places we're

42:09

we're talking about.

42:11

>> But it also gets at a core truth which

42:13

is people don't actually want data

42:15

centers around them. It is a cost. It is

42:17

a concentrated cost for a diffuse

42:19

benefit.

42:20

>> Like if you believe in the benefit.

42:22

>> Yeah.

42:22

>> So I think that's part of it.

42:24

>> I want to go back to the first bucket

42:25

you were talking about which is like the

42:26

race dynamics.

42:27

>> Yes.

42:28

So, at the most generous, the thing that

42:31

I've heard repeatedly is sort of what

42:33

you're describing, which is it would be

42:36

better if this were going slower,

42:39

but I can't control that because I

42:42

whether I'm at, you know, Anthropic or

42:46

Open AI or Google or Meta,

42:49

>> you know, if we slow down, it just is

42:52

our less ethical competitors over there

42:54

who speed up. And even if you put down

42:57

legislation slowing down all of America,

43:00

then it's China,

43:01

>> right?

43:01

>> You know, the CCP

43:03

which is going to to win the race.

43:07

>> I guess one question is, do you buy this

43:10

central metaphor of a race that has a

43:14

like a ticker tape line where at some

43:16

point somebody passes it and then they

43:17

have the recursive super intelligence

43:19

and like the race is over? Or do you see

43:22

this more as like most technologies like

43:25

a kind of like a linear

43:27

set of gains? I mean can be fast, can be

43:30

slow, but that doesn't have that

43:33

somebody is going to win dynamic.

43:36

>> Yeah, I find this really confusing. One

43:38

of the first things that I um did when I

43:41

started reporting more deeply on AI was

43:43

try to figure out what AGI meant because

43:46

a lot of the way that this race has been

43:48

characterized is who will build AGI

43:50

first? who build artificial artificial

43:52

general intelligence first. Um thing

43:54

first thing I found no one agrees on

43:56

what that means. Uh AGI means everything

43:59

from techn AI that can build itself to

44:01

AI that can do all human jobs to AI that

44:04

produces whatever number of economic

44:05

value. Um and so everyone has these

44:08

different milestones for what

44:10

constitutes AGI to them. What that also

44:12

means is that the race has different

44:14

finish lines and moving finish lines.

44:15

And I think that like you see the way

44:18

that these uh models perform differently

44:20

on benchmarks. They are extremely

44:22

jagged. They can be super good at math

44:24

and they can be super bad at poker at

44:26

the same time. Um they can be yeah

44:28

amazing at cracking cyber security

44:31

problems but not able to build anything

44:33

in the physical world. And because of

44:35

that I don't think that technology is a

44:37

as general as people suggest it is. I

44:40

also think that means that it is much

44:43

harder to define a finish line to the

44:45

race and my sense is that the race

44:48

because you cannot adjudicate it,

44:50

everyone will always feel that they are

44:52

falling behind on some dimension. I mean

44:55

to then make the case for that these AI

44:57

companies are making is they do believe

44:59

in this recursive self-improvement. They

45:01

think that you know OpenAI, Google, deep

45:03

mind and anthropic are all extremely

45:04

focused specifically on the question of

45:06

can we build AI that builds itself? Can

45:08

we build an AI that can train the next

45:11

generation model completely from scratch

45:14

on its own? And in that sense, you get

45:16

an exponential pace of improvement for

45:19

whoever can hit that recursive

45:22

self-improvement curve first. And they

45:24

think that this might lead to that

45:26

company pulling ahead. Right now, folks

45:29

think that it's anthropic, which has the

45:30

best coding models, meaning they can

45:32

code faster, meaning that their next

45:33

models are even better.

45:36

I can see where that argument is, but

45:41

I'm not sure when we look at, you know,

45:44

the latest anthropic models versus the

45:46

latest open AAI models versus the

45:47

latest, you know, Chinese open weights

45:50

models that we see a company pulling

45:52

ahead that decisively in that way,

45:54

especially when every single company in

45:56

lab is using the same recursive

45:58

self-improvement strategy. And so,

46:01

basically, I don't know that the race

46:03

has a finish line. And that's what

46:04

worries me about it continuing.

46:06

>> The reason I want to focus in on this

46:08

race metaphor for a minute is I've come

46:10

to think it is really one of the central

46:13

dividing lines in how you think about

46:15

different kinds of AI policy.

46:18

>> Whether you think that we are in a race

46:20

with China to get to the point where one

46:24

side or the other is going to pull like

46:25

endlessly and decisively ahead because

46:27

they hit that, you know, recursive

46:29

self-improving level.

46:32

Well, then that means what you do in the

46:34

next 1 to 3 years is incredibly

46:38

incredibly definitionally important.

46:40

[sighs]

46:41

>> But if you don't believe that, if you

46:42

believe something more like yes, this is

46:44

a powerful technology. It's a powerful

46:46

technology that might have a lot of

46:47

downsides, might come with a lot of

46:48

social instability.

46:50

Um, its effect on a society may not be

46:53

good. then

46:56

let's run faster to the bad place is not

46:59

nearly as compelling an argument. And

47:02

all of a sudden the idea that we should

47:05

have policy in place that slows things

47:08

down for more voice for more

47:09

consideration.

47:11

It's not crazy. And I guess one place

47:13

this goes is that I have begun to notice

47:15

like a really interesting convergence

47:18

between the SFAI safety people

47:22

>> in a way and like the AI populace like a

47:24

Bernie Sanders or in a different way

47:26

Abdul Alad

47:27

>> who are getting to not that different

47:30

places but through very very different

47:34

mechanisms right they're like the AI

47:35

safety people who actually believe we

47:37

are in a race

47:38

>> but they believe that winning that race

47:40

might bring the end of humanity Right.

47:43

>> And so like they don't they don't want

47:44

to move that fast, right? If we began to

47:46

slow down, we would have more

47:47

credibility for negotiating with China

47:49

and like trying to come up with like

47:50

international treaties and all the rest

47:52

of it, you know? And then you have like

47:53

the kind of more AI populous side who

47:56

just like doesn't want to give all these

47:58

tech billionaires all this power, who

47:59

doesn't believe this technology will be

48:00

good for people, and they're starting to

48:02

come up with like maybe not the policies

48:04

AI safety people would, but you know,

48:06

data center moratoriums and things like

48:08

that.

48:09

And so you have this sort of slightly

48:11

strange

48:12

like you would not have considered this

48:14

coalition.

48:15

>> It's super interesting. I mean you

48:17

literally have Ronda Santis doing AI

48:20

roundts with Max Tegmark who's been one

48:22

of the leading advocates of pausing and

48:24

slowing down AI, an MIT professor, and

48:27

you have Bernie Sanders doing viral

48:30

videos with Eleazar Yudkowski. Um the

48:32

guy who's telling us that AI is probably

48:34

going to kill us all if we build it. Um,

48:36

I was talking

48:37

>> just both in lines and doesn't and does

48:38

kind of makes it, you know what I mean?

48:40

[laughter]

48:40

>> Yeah, totally. I've been spending some

48:41

time in DC this year to talk to some of

48:43

these AI populists, some from the social

48:45

conservative right, others from say the

48:46

labor left. And um, this Bannon guy I

48:49

was talking to told me he's like, you

48:50

know, like I wouldn't send my kids over

48:52

to a playday at the polycule, but I can

48:54

do coalitions. And so I think it's been

48:57

one of the most interesting uh,

48:58

political stories going on right now is

49:00

the sort of strange bedfellows that have

49:02

emerged. I mean, even with the data

49:04

center stuff, I was talking to an

49:05

activist and they were saying these were

49:06

liberal women who had gotten into

49:08

politics after the 2016 election of

49:10

Donald Trump. They said that data

49:11

centers were the first thing that got

49:12

them to talk productively with their

49:14

Trump voting neighbors about politics,

49:15

the first thing in like 10 years almost,

49:17

which is fascinating to me. And in this

49:19

sense, they felt a really strong sense

49:21

almost of uh political agency that

49:24

almost came out of this fight. Um, so I,

49:27

yeah, I think one of the big questions

49:29

that folks in AI safety, for example,

49:30

are thinking about is, do we want to

49:33

build these alliances with the rising

49:35

left and right populist waves in

49:37

American culture in order to slow AI

49:40

down? Maybe it's okay that we have

49:41

different reasons and different theories

49:43

for why AI is so dangerous. For one

49:45

person, is big model bad. For another

49:48

person, it's big billionaires bad, big

49:49

tech bad. Um and those folks are sort of

49:53

linking arms in a lot of ways against uh

49:56

the AI accelerationists and sort of the

50:00

folks pushing the race faster. So I

50:02

think it listening to this we've been

50:04

sort of living in the data center

50:07

moratorum side of the politics.

50:10

But what's the other side of it? What

50:12

are the problems with just saying okay

50:14

fine like let's not build any more data

50:16

centers?

50:17

one like this is not actually the way

50:20

that you would successfully slow down AI

50:22

if that's what you really wanted. Um one

50:25

if you if one locality or one state

50:27

imposes a moratorum AI companies are

50:30

very very happy to go to other states or

50:32

other countries. They are already

50:33

flooding into Texas for example because

50:35

it's had such a pro data center

50:36

environment. People are looking at

50:37

Louisiana, the Dakotas, Australia. Um,

50:40

space of course is a current big

50:42

interest of Elon Musk's because people

50:45

think that maybe not now but in five

50:47

years we can just put all the data

50:48

centers in space and solve the political

50:50

problems that way. So one is I'm not

50:52

really sure that this would stop AI

50:54

progress that much. It would just shift

50:56

the data centers to other places that do

50:58

welcome them. Um the second thing is I

51:02

actually do think that there are ways

51:06

for these deals to be good. Not every

51:08

community should want to data center. I

51:10

think that many of them may discuss it

51:13

and say this isn't what we want. We

51:15

don't need the tax revenue that bad. But

51:17

in a lot of the cases with these sites

51:19

that I visited like you know in the old

51:22

GM site in Jainsville, the Vidian

51:25

Partners, the data center developer was

51:27

going to clean that brownfield up. They

51:28

were the only ones willing to do so. I

51:30

talked to a real estate broker who had

51:31

tried to sell the site for 5 years and

51:32

he couldn't do it because not a single

51:34

other commercial buyer wanted to clean

51:35

up all of this hazardous waste. Only the

51:37

data centers were willing to do that. Or

51:39

with Mount Pleasanton, the Foxcon site,

51:41

right? They had already cleared all this

51:43

land. They had built all this

51:44

infrastructure. Putting a data center

51:47

there was a net improvement for the

51:50

community most in my opinion personally

51:52

from an economic perspective, from the

51:53

perspective of there was nothing going

51:55

on there anyway. Um, so I think that

51:57

there are ways to do these deals, right?

52:00

There is enough money in this industry

52:01

that a lot of communities will decide it

52:03

is economically beneficial for them to

52:04

bring in these jobs and bring in this

52:06

investment. But I think that the way

52:08

that the data center deals have been

52:09

done nearly guarantee the amount of

52:11

public backlash that there's been. And

52:13

the thing that will probably fix it, I

52:15

suspect, is probably um either like a

52:17

state level streamlining where someone

52:19

does the research probably at the state

52:21

level, maybe at the federal level to

52:23

figure out what is the fair way to do

52:24

these deals. How do we ensure the

52:26

communities get the most transparency,

52:28

the most benefit out of data center

52:29

deals when they happen? So it's not case

52:31

by case and it's not so asymmetric with

52:32

a town of 12,000 negotiating with an

52:34

open AI or whatever.

52:36

>> I would add two other things to that

52:38

that I'd be curious to hear your take

52:39

on. So one you mentioned data centers

52:41

moving towards other localities and

52:43

those localities are not randomly

52:45

selected. They're localities that are

52:47

going to impose fewer conditions. So

52:50

maybe that is fewer environmental

52:51

conditions but you know in the case of

52:53

maybe a UAE or some of the Gulf states

52:55

that are interested here you know you're

52:57

looking at more authoritarian countries

52:58

right so I've heard a lot of people

52:59

worry about that or you know Elon Musk

53:01

in space. Uh so in a sense if you make

53:05

it so the data centers cannot go into

53:07

places where there is more democratic

53:09

control they might you might end up with

53:11

less overall democratic control. The

53:14

other thing and and I do think this is

53:15

significant is that there is right now

53:19

more demand

53:20

>> for compute than there is compute.

53:22

>> Yes.

53:23

>> You know people talk a lot about a

53:24

bubble but we do not look to have excess

53:26

AI supply at the moment. Mhm.

53:29

>> And if demand keeps rising because you

53:31

know the coding agents get better and

53:33

all the rest of the things we know that

53:34

are happening but you are constricting

53:38

the supply of compute

53:41

then you end up with more inequality and

53:43

who can afford it. So you know a Goldman

53:46

Sachs a JP Morgan right so you know a

53:48

company with a lot of money to buy

53:50

compute is going to have a lot of it and

53:51

then you know ordinary users small

53:53

businesses etc. If you believe AI is

53:56

important and powerful and I believe it

53:58

is important and powerful then you have

54:01

a problem where you have created much

54:03

more stratification and who can afford

54:05

it. How do you think about those

54:06

dimensions of it?

54:08

I think with where you build the data

54:10

centers, a lot of folks are starting to

54:12

look at building AI infrastructure as a

54:14

form of geopolitical leverage, right?

54:16

And so some countries like places like

54:19

Australia, Canada, um countries in

54:21

Europe are thinking actually maybe the

54:24

way for us to get a slice of Frontier

54:25

AI, for us to negotiate with uh the

54:28

countries where the best AI is being

54:29

developed like the US for in cases like

54:32

cyber security access um is to say, you

54:35

know, we'll build your data centers

54:37

here. will actually welcome you in and

54:39

in return uh maybe you guarantee us

54:41

access to the frontier models. Um so I

54:44

think that one is that we should look at

54:46

a AI infrastructure as a point of

54:49

leverage um that both states and

54:51

countries have and as you mentioned if

54:55

local moratoriums in the US if domestic

54:58

moratoriums or something like that lead

55:00

to giving that leverage and negotiating

55:02

power to authoritarian states that's

55:05

probably something the US should be

55:06

really worried about. On the other hand,

55:08

there are folks like um Anton light at

55:10

Carnegie has done work on this where

55:12

it's can we give our allies, can we give

55:14

our democratic allies um negotiating

55:16

leverage through them building out

55:19

compute. The second thing that you

55:20

mentioned about pricing is interesting

55:22

because I do think one of the big macro

55:25

trends in AI right now is the closing of

55:28

the frontier. It's the fact that the

55:30

very best models like mythos from

55:32

anthropic are not being open to

55:35

everybody. That is both a safety

55:37

decision as in we don't want to give

55:40

really powerful cyber weapons and

55:41

bioweapons to a bunch of bad actors or

55:43

just unknown actors. It is also a

55:45

pricing question of the best models are

55:48

really really expensive to run. They

55:49

don't have enough compute to run them.

55:52

And so we're going to have to charge a

55:54

lot of money or only give it to the

55:55

biggest corporations. And I think that's

55:57

a reason that startups are worried uh

56:01

that countries outside of the US are

56:03

worried that normal people are worried

56:06

maybe we get super intelligence and I

56:08

can achieve all these amazing things but

56:11

I'm not going to get it. Maybe my boss

56:12

is going to get the super intelligence

56:14

and they're going to automate my job but

56:15

as a worker as a consumer I'm not going

56:18

to be able to do the same thing. So I

56:19

think it's also a really good point that

56:21

if we don't continue the compute

56:23

buildout, we do see a world where it is

56:25

the folks with existing capital and

56:27

access probably big corporations in the

56:29

US and the US government that are going

56:31

to have access to Frontier AI and all

56:33

the benefits that it confers.

56:35

>> You were in China for a trip reporting

56:38

on AI. Was there much political AI

56:40

backlash and ferment there from what you

56:44

could see? I was super interested in

56:45

this question on this trip because I was

56:47

finishing my times piece on the

56:48

permanent underclass while in China. And

56:50

so I was basically asking everyone I met

56:52

there, whether it was engineers at the

56:53

labs or just my family members or sort

56:55

of normal middle- class people in

56:56

Shanghai. Um, are people worried about

56:58

AI and jobs? Um, are people worried

57:00

about AI and social instability? Um, I

57:03

think the answer is not as much. I

57:05

caveat this of course with the fact that

57:07

the information environment in China is

57:09

obviously suppressed. you can't uh

57:11

dissent um in public on social media

57:13

nearly as much as you can in the US. You

57:15

don't have good polling. So, it's kind

57:16

of hard to understand the actual level

57:18

of social discontent there is in China.

57:20

But I would say that for the most part,

57:22

people were not as terrified of AI as

57:25

they are in the US. Um there's a few

57:27

explanations for this. Some people say

57:28

that China is more technoptimistic than

57:31

the US is. I don't love this explanation

57:33

mostly because the thing that I heard

57:34

was not exactly optimism. It was not

57:36

exactly, yeah, we're going to get the

57:37

cancer cures and the super abundance. It

57:39

was something a lot closer to

57:42

technology is a force that cannot be

57:44

stopped. It actually in some ways

57:45

reminded me more of some of these

57:46

Silicon Valley beliefs that the future

57:48

is predetermined that when the state

57:50

decides that something like AI is a

57:52

national priority that is going to march

57:54

forward and as an individual there's not

57:55

much you can do to resist especially in

57:57

a one party state in a authoritarian

57:59

society there is no culture of

58:01

resistance really and so rather than

58:04

thinking about how do I prevent AI in my

58:07

workplace or in the world that's not

58:08

really a thing that a lot of people in

58:10

China think about it's how can I use AI

58:12

to make sure I don't fall behind. in an

58:14

environment that already has crazy

58:16

levels of white collar competition and

58:18

white collar unemployment. If you're if

58:20

you're not upskilling yourself with, you

58:22

know, open claw or whatever, there's a

58:24

million people in line behind you who

58:26

are going to get on the bus. At the same

58:28

time, I think that the Chinese state

58:29

takes a pretty different approach to the

58:30

US. Um, when it comes to AI regulation

58:32

and also to technology regulation in

58:34

general. And so, uh, China has passed

58:37

laws sort of banning a lot of kinds of

58:38

companion chat bots because they're

58:40

worried about relationships. They're

58:41

worried about fertility rates. um

58:43

they're worried about addiction. Uh

58:46

China has passed uh made court rulings

58:49

that say that AI replaced this worker's

58:52

job. AI can do this worker's job is not

58:53

a good enough reason to lay off a

58:55

worker. Um you have regulations that

58:58

require all AI generated images to be

59:00

labeled and you'll see the made with AI

59:02

sort of language on all of the AI made

59:04

ads in China. And so there's also a

59:06

sense that some people, some Chinese

59:08

have that their government is more

59:10

likely to look out for sort of the

59:12

social downsides and the labor downsides

59:15

relative to the US government which has

59:17

thus far been pretty less a fair

59:19

especially at the national level. Right.

59:21

And that gives some people a bit of

59:23

soulless as well.

59:24

>> There's been some reporting that China

59:26

and Russia are pushing sort of anti-data

59:30

center oh yeah

59:31

>> memes and you know social media bots. Uh

59:35

it's hard for me to tell what scale that

59:37

is, but it has been very much picked up

59:39

on by like people like Kevin Olri the

59:41

for the Shark Tank guy who's you know

59:43

big data center project has faced a lot

59:45

of backlash.

59:47

>> Do you buy the the sort of growing view

59:50

among like at least some tech elite that

59:52

the data center backlash is like a

59:53

Chinese scop?

59:54

>> I think this is ridiculous to be honest.

59:56

I mean, so I read the OpenAI report that

59:58

was saying like this is all a CCP plot

60:01

and like it pastes in the accounts and

60:04

the tweets that are doing the SCOP.

60:06

These tweets have like no likes on them.

60:07

They have two views per tweet. So I'm

60:10

not doubting that. Like I'm sure some

60:12

clever CCP propaganda person has

60:14

attempted to inflame the anti-data

60:17

center sentiment. I have not seen

60:19

evidence that any of this is working. I

60:21

think it feels very organic. I think I

60:23

also tend to be personally a little

60:24

suspicious when you just castle your

60:26

political opponents as being

60:27

misinformed. I think there's a way in

60:29

which people use foreign influence to

60:31

avoid thinking about the fact that there

60:33

are people that they live with in

60:35

society who do not agree with their

60:36

vision of the world. And when I talk to

60:38

these uh data center activists for

60:41

example, they are actually much less Tik

60:42

Tok adult and misinformed than I think

60:44

people like to caricature. A lot of them

60:46

understand sort of the basic facts of

60:48

what's the difference between an AI data

60:50

center and the old kind of data center.

60:51

how much what's the difference between a

60:52

closed loop system and an openloop

60:54

system? Most of these people are not

60:55

just misinformed. They have just

60:57

personally decided I'm not that

60:59

interested in having a data center in my

61:01

community even if it pays some property

61:02

taxes.

61:03

>> So when you talk to people in the AI

61:06

companies and and sort of talk to them

61:09

about this backlash, I know they're very

61:10

worried about this, right? I've talked

61:11

to them about this.

61:13

>> What are they learning from it? I do

61:17

think that this year in 2026,

61:21

I've AI executives, AI researchers have

61:24

started to take the public backlash a

61:27

lot more seriously than they have in the

61:29

past. Um, I've heard executives ask,

61:32

"Can we do better marketing? I don't

61:34

understand why it is that Whimos are so

61:36

unpopular." Um, I've heard executives

61:39

ask, "What do you think are the deals

61:41

that we should be making? Do you think

61:43

we should just be mailing checks to

61:44

every house that lives near a data

61:47

center project? Will that fix things?

61:49

Um, like tell us how to make a better

61:51

deal. Do we need to cut people's

61:53

electricity prices in half? Would that

61:55

work? Unfortunately, the word bribe gets

61:57

used a lot more than I am personally

61:59

comfortable with. I think that when you

62:00

are framing the thing you're doing, even

62:02

jokingly, as bribing communities into

62:04

putting a data center there, I don't

62:06

think you're starting off on the right

62:07

foot. Um, I think that people can feel

62:09

when they are being bribed. I've heard

62:11

these people say these companies are

62:12

biting us. Um, so there's a little bit

62:16

of examination. The thing that I don't

62:18

think is being examined as much as I

62:20

want it to be though is are we building

62:23

a technology? Are we building a product

62:25

that is helping people?

62:26

>> Yeah. The version of this I have heard

62:28

is we have a marketing problem. Maybe we

62:31

should stop saying aloud so often.

62:34

>> Yes. that our technology might take

62:36

everybody's job and has a 10% chance of

62:40

upending or destroying humanity

62:43

altogether.

62:47

What has not been clear to me even as

62:49

they begin to like maybe move away from

62:50

that messaging a little bit is whether

62:54

or not they no longer believe that.

62:57

Again, I am my personal view is like I

63:00

don't think it's going to take

63:01

everybody's job. But to the extent they

63:04

do or at least they take that very very

63:05

seriously, it's like I keep hearing them

63:07

say that we have a marketing problem.

63:09

And I keep saying when I talk to them

63:10

about this

63:11

>> that if you believe the things you have

63:13

been saying and in fact the things you

63:14

have told me personally,

63:15

>> you don't have a marketing problem.

63:17

>> Yeah.

63:18

>> You have a problematic technology like

63:20

you have a product problem.

63:22

>> Yes.

63:22

>> Because people are not going to want

63:23

that future.

63:24

>> Yeah. I mean, I think I would make some

63:27

distinctions between, of course,

63:28

different companies, different

63:29

executives, right? Like one thing that's

63:31

like very interesting to me thinking

63:32

about the comms in Silicon Valley is

63:34

that for a very long time, these

63:36

companies were only marketing to

63:39

potential recruits and potential

63:40

investors. Basically, they were trying

63:42

to win the vibes on AI Twitter in San

63:45

Francisco. And I kind of feel like they

63:47

never realized everyone else could hear

63:48

them, right? And so now they're trying

63:50

to take it back. But like my sense is

63:51

that Sam Alman for a long time part of

63:53

the reason he was talking about like oh

63:55

shifting the balance of power from labor

63:56

to capital and like rogue AI and

63:58

whatever was also because he was winning

64:00

points among people who he wanted to

64:02

work at open AI and he had to

64:04

communicate that he was as agi pill as

64:05

them. He was as worried about the same

64:07

safety things as them and now that his

64:10

interest is more in political goodwill

64:12

and IPOing and things like that he's

64:15

sort of changed his tune. Um, I think

64:17

that, yeah, I I'm I'm not sure to what

64:20

extent every AI industry actor has

64:23

always believed the things that they've

64:25

warned about.

64:26

>> I think people can believe things they

64:28

don't feel, if that makes sense.

64:31

>> And I think a lot of people in the eye

64:34

industry are in a culture and inside

64:37

arguments where

64:39

this set of outcomes feels very real,

64:41

right? Uh or or looks very real. And so

64:45

I think they believe it. I think when

64:46

they make these arguments, I don't think

64:48

they're just doing it for, you know,

64:50

publicity points. In fact, I think it's

64:51

the opposite. I think when they're now

64:53

trying to move away from some of these

64:54

arguments, I think it's actually much

64:55

more of like a cynical marketing ploy.

64:57

>> Yeah.

64:58

>> But I think they often believe these

64:59

things without actually like in their

65:01

bones,

65:03

>> feeling it.

65:04

>> Um, which is sort of why they act

65:07

>> relatively heedlessly.

65:08

>> Yeah. or at least like on the set of

65:10

things they believe like this

65:13

speculative notional set of beliefs

65:14

about what might happen is way less

65:17

close to their core. Yeah.

65:18

>> Than their belief that if they don't

65:19

build this data center or get this next

65:21

model out like their competitors or

65:23

China or somebody Yeah.

65:25

>> is like going to get in front of them

65:26

and they're much more motivated by by by

65:28

the push forward.

65:29

>> Yeah. I mean I think the technological

65:31

determinism is just such a big part of

65:32

it. I think that if I'm trying to think

65:34

about how my friends in the AI industry

65:36

would react to this conversation, that's

65:37

the thing that they would say that we

65:38

are not focusing on enough is they are

65:40

so sure that there is no way that AGI or

65:42

super intelligence or whatever it is

65:44

does not get built and it is only a

65:46

question of who builds it. I think that

65:48

fundamental sort of underlying belief is

65:51

what justifies everything else is we

65:52

have to be the ones to do it. Us pulling

65:55

back, us stopping is not going to

65:56

prevent any of the bad stuff. Right. I I

65:58

agree with that and I think that's why

66:00

the China card in this has been such

66:02

like a destructive part of the argument.

66:04

I'm not even sure it's totally untrue.

66:05

Like I I am completely willing to

66:07

believe that China and America are in a

66:09

race for a economically and

66:11

geopolitically important technology even

66:13

if you don't buy like recursive super

66:15

intelligence. Mhm.

66:16

>> Um

66:18

but the way that has then been used to

66:20

not say well we should enter into

66:23

international negotiations or something

66:24

but instead just like we cannot slow

66:27

down whatsoever no matter what else we

66:29

worry about or or believe I think has

66:30

been it is it is acted as a kind of of

66:33

blackmail and the thing is that it's not

66:36

bought by enough people no

66:38

>> outside of the industry but I think the

66:42

phase of the politics we're now in is

66:44

out of their control And it is just not

66:47

going to be the case that they have

66:50

control over the AI narrative like next

66:53

year that they had two years ago. And

66:57

yeah, I don't really think they know

66:58

what to what to do in that space. And so

67:00

now it's like either going to have to

67:02

start benefiting

67:03

>> Yeah.

67:04

>> people, right? You some of these like if

67:07

people began seeing like drug cures come

67:08

out, right? All these things we've

67:10

actually been promised, right?

67:11

>> And you could say like we're beginning

67:12

to see the beginning of like

67:13

mathematical conjectures. Like that's

67:14

been pretty cool, but we're not really

67:17

seeing the gains. And if you start

67:19

getting the losses before the gains,

67:21

right? You start getting the job loss,

67:22

for instance, before the promised, you

67:24

know, super abundance,

67:26

>> politically, that's not going to be an

67:27

equilibrium you can protect.

67:29

>> That's one of the things I'm worried

67:30

about is I do think that we are pretty

67:32

likely to see we are seeing a lot of the

67:34

social instability before we get the

67:37

cancer cures, right? And so or even with

67:40

the math stuff, it's like I think that

67:42

one thing I notice more and more now is

67:44

this deep cultural and values gap

67:46

between Silicon Valley and the rest of

67:48

America, the rest of the world. I'm not

67:50

saying that Silicon Valley is wrong,

67:51

that it's cool to like disprove the

67:53

Jacobian conjecture, right? Like um it

67:55

is cool, but like when you ask a lot of

67:58

people in the tech industry what their

68:00

utopia looks like, they'll say things

68:01

like, "We have UBI, so no one has to

68:04

work anymore. or we're all immortal and

68:06

we've discovered all of math and

68:07

physics. And if you do the polling on

68:09

UBI and immortality, neither are

68:11

especially popular with the American

68:13

public. I think that

68:14

>> we pulled immortality is a [laughter]

68:15

funny

68:16

>> I mean it's been pulled. You can look it

68:18

up. Um if you ask people what like they

68:21

want AI to do for them, it's not

68:24

necessarily having you know parents tow

68:26

in your pocket. It's not disproving

68:28

math, right? Like they want things to be

68:30

cheaper. They want to be healthier. They

68:32

want to not do crappy work so they have

68:34

more time for the stuff they like. But I

68:36

think it is genuinely true that the

68:38

stuff that is really cool and also that

68:40

it's oftentimes technically easier to

68:42

solve like math um is not what most

68:47

people want from this technology. Um and

68:49

I think it's also true that it's just

68:50

literally technically harder to cure

68:53

cancer than it is it turns out to prove

68:56

math theorems. And the other thing that

68:58

I hear from the public when I talk about

69:00

the cancer cures is, yeah, but are they

69:03

going to just use it for themselves? Is

69:04

Peter Teal or whoever just gonna buy

69:06

himself immortality? Am I going to be

69:08

able to afford immortality?

69:10

>> My view for a very long time has been

69:12

that a lot of people in these companies

69:15

overrate how much of the bottleneck in

69:19

scientific and human progress is raw

69:20

intelligence.

69:21

>> Yes. Yeah.

69:22

>> And just I mean this is a point of

69:23

abundance. just but the point of

69:25

covering anything anywhere

69:27

>> the world is full of friction.

69:29

>> Yeah.

69:30

>> And you know you want to do drug

69:32

discovery and I think we should actually

69:33

do a lot to make drug discovery easier,

69:35

make drug testing easier, right? Like I

69:37

have said this many times before, I

69:39

would like to see us prepare like drug

69:42

development for a world where AI is

69:45

spitting out way more promising

69:47

molecular candidates.

69:49

>> But that's still a world where you need

69:50

enough monkeys to test things on,

69:52

>> right? humans to test things on, rats to

69:54

test things on, right? And you still

69:55

need to do all the safety data and just

69:58

the amount of the world that is slowed

70:00

down by we don't have any good ideas

70:02

like we are out of ideas versus

70:05

it is hard to organize things uh amidst

70:08

humans you know amidst you know with raw

70:11

materials like in bureaucracies in

70:14

organizations you get like intelligence

70:16

is important um but it is not everything

70:21

and I think anybody who's like been in

70:23

organizations like knows It's actually

70:25

less than you think it is.

70:26

>> Yeah. Again, I think of a, you know, a

70:28

lot of these people have been AI

70:30

researchers for their entire careers.

70:31

Maybe before that they were physics PhDs

70:34

or they were uh doing quant trading

70:36

which are all these kinds of jobs that

70:38

are fairly they're IC jobs or individual

70:40

contributors where you're not

70:41

necessarily working in big teams. So

70:43

there's not a lot of politicking and

70:44

relational work where all of the

70:46

relevant context lives inside a single

70:48

codebase. And so for AI to sort of

70:51

understand what's going on, it can kind

70:52

of explore all this context that's

70:54

already been written down. I'm not

70:55

saying there's no tacet knowledge, but a

70:57

lot more of the context is made

70:59

explicit. And these are also places

71:00

where simply applying more thinking and

71:03

more intelligence just as an individual

71:04

like as a person, a remote worker in a

71:06

closet or whatever might actually find

71:09

the more efficient algorithm, right?

71:10

Like you don't actually need to politic

71:12

your way to a better algorithm. You

71:14

don't need to do stuff in the physical

71:16

world to get that. And so I think a lot

71:17

of people at these companies don't

71:21

really realize how hard that is. cuz I

71:22

mean it's funny cuz people will say

71:24

things like um yeah there's like

71:26

electricity cost and energy cost to AI

71:29

but like AI will maybe solve the climate

71:32

and I ask how and to be clear I think

71:34

there are a lot of ways that AI can

71:35

improve you know climate science

71:37

research help

71:37

>> yeah building efficiency

71:40

but like at the same time you ask people

71:42

and it's just like oh I don't know it's

71:43

just going to do it right or it's like

71:45

oh how how is AI going to improve

71:46

robotics like I don't know AI will

71:49

figure it out you kind of do have this I

71:51

I find it lazy actually like I one of

71:53

the things that annoys me about this

71:54

particular approach is it's not that I

71:57

don't think that AI can contribute to

71:58

all of these problems. I think it

71:59

definitely can but what I often hear is

72:01

a kind of laziness about how it's going

72:03

to do that and it feels like a DSX mocka

72:06

of it's super smart it'll just figure it

72:08

out.

72:08

>> I used to say that this was back when

72:10

you know Silicon Valley was a more

72:12

optimistic place than it has been in

72:13

recent years. uh but that the difference

72:15

between the culture of DC where I live

72:17

for a long time and of Silicon Valley

72:20

was that in Silicon Valley people's

72:22

worldview is formed by seeing impossible

72:26

problems prove possible to solve and in

72:30

DC people's worldview is formed by

72:32

seeing possible problems prove

72:34

impossible to solve and I think that is

72:38

now going to collapse for the AI

72:39

industry into one worldview because you

72:41

know these are people who like give them

72:43

their due

72:44

They've invented artificial

72:45

intelligence. Like they actually did it.

72:47

>> You know, this is amazing. Like I cannot

72:50

believe how good some of these systems

72:52

are. I'm like shocked to be living

72:54

through this.

72:55

>> They were able to do that. That seemed

72:56

impossible proved possible. And now

72:58

they're going to now they're finding

72:59

it's like impossible to build a data

73:00

center.

73:01

>> Yeah. [laughter]

73:02

>> And like that's what doing other kinds

73:05

of things in the world teaches you.

73:07

>> Yes.

73:08

>> That there are a lot of problems that

73:09

are not possible to solve. Not because

73:12

like you cannot come up with the idea

73:13

for them

73:14

>> but because you are dealing with like

73:17

the messy realities of societies of

73:20

politics of values of you know um

73:22

logistics

73:24

>> and um it'll demand a kind of it'll

73:28

impose a kind of realism I think on the

73:31

industries that it has not always had.

73:33

>> Yeah. I was trying to think about what

73:35

the difference was between how I would

73:37

describe Silicon Valley and San

73:38

Francisco culture a year ago. um let's

73:41

say early 2025 versus now. And I think

73:44

the number one thing is that Silicon

73:45

Valley has really woken up to politics.

73:47

Um you know, in January 2025, Silicon

73:50

Valley was feeling very triumphant about

73:52

about Doge, about Elon Musk, about David

73:54

Sax and Trurom and the White House. It

73:56

kind of felt like they were all in

73:57

control. And actually, if you just build

74:00

the these genius technologies and you

74:02

get super rich and you have good ideas,

74:04

you'll just, you know, get the political

74:06

power to enact your vision. And a year

74:08

and a half later, a lot of those folks

74:10

are out of the White House. They failed

74:12

at reducing the national debt and

74:13

achieving all these other goals that

74:15

they thought they could just AI their

74:16

way into solving. Um, Anthropic, for

74:18

example, um, is has had a lot of

74:21

problems in its dealings with the Trump

74:23

administration, fundamentally very

74:25

political and very relational problems.

74:27

>> Daario's problem in dealing with the

74:29

White House was not, I think, that he

74:31

didn't have good arguments or that he's

74:32

not very smart or not saying logical

74:34

things. Um, I think that anyone from

74:36

anthropic will admit that these are

74:37

largely relational problems. And so

74:40

there's a way where I think democracy

74:42

and politics is a lot more powerful than

74:45

these very rich and very smart tech

74:47

people realize. Um, and there's some

74:50

optimism to that, I think, and in in

74:52

looking at it and saying it's actually

74:53

really hard to buy an election. It's

74:55

actually really hard to buy out the

74:56

whole White House at once. Um, but it's

74:59

an interesting moment I think for uh the

75:02

tech industry to be realizing how

75:04

important politics really is and how

75:06

difficult it is.

75:07

>> I think that's a good place to end.

75:08

Always a final question. What are three

75:10

books you'd recommend to the audience?

75:12

>> Oo. Um, so I think the first one is

75:14

really relevant to this conversation

75:15

which is uh Benjamin Lobitudes the

75:17

Maniac um which includes a sort of

75:20

lightly fictionalized biography of John

75:21

vonman the story of AlphaGo. I think

75:23

it's very much a sort of halfway novel,

75:27

halfway non-fiction book about how

75:30

intelligence is incredibly all inspiring

75:33

and something worth respecting and at

75:35

the same time can lead people to some

75:38

very dark realities. Um, my second book

75:42

is The Technology Trap from Carl

75:44

Benedict Trey, which I think is very

75:47

much about how people's attitudes

75:49

towards technology and automation depend

75:52

on to what extent the benefits, the

75:55

economic growth is shared, to what

75:57

extent they feel like they're getting a

75:58

piece of the pie. It goes through a lot

76:00

of history, much more than just the

76:01

industrial revolution. And so that's

76:02

shaped a lot of my thinking on some of

76:04

the economic questions and the populist

76:06

questions. Um, and then finally, uh,

76:09

Pria Parker's The Art of Gathering

76:11

because I do think that the relational

76:13

stuff is going to become a lot more

76:15

important. It always was, and I do think

76:18

that book has helped me become a better

76:19

host.

76:20

>> She would be so happy to hear that.

76:21

People should go check out our

76:22

conversation with Pria Parker. Jasmine

76:24

Sun, thank you so much.

76:26

>> Thank you so much for having me. This is

76:27

fun.

76:30

[music]

Interactive Summary

The video discusses the growing public and bipartisan backlash against the construction of massive AI data centers across the United States. Journalist Jasmine Sun explains that this opposition is fueled by the unsightly, industrial nature of these facilities, concerns over energy and water consumption, the use of non-disclosure agreements that alienate local communities, and a broader 'AI populism.' This sentiment reflects a deeper distrust in both government and big tech companies, as local communities feel like they are bearing the costs of a project for which they see no direct benefit, or that is being forced upon them by powerful, unaccountable actors. The discussion also touches upon the existential risks and economic anxieties associated with AI, the competitive 'arms race' mentality that drives these companies to act heedlessly, and the political limitations of Silicon Valley's attempt to use wealth to override democratic processes.

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