This is democracyow [music]
democracynow.org
the War and Peace Report. I'm Amy
Goodman. The Empire of AI, that's the
name of a new book by journalist Karen
How, who's been closely reporting on the
rise of the artificial intelligence
industry with a focus on Sam Alman's
Open AI. That's the company behind Chat
GPT. Karen how compares the actions of
the AI industry to those of colonial
powers of the past. She writes, quote,
"The empires of AI are not engaged in
the same overt violence and brutality
that marked this history, but they too
seize and extract precious resources to
feed their vision of artificial
intelligence. the work of artists and
writers, the data of countless
individuals posting about their
experiences and observations online, the
land, energy, and water required to
house and run massive data centers and
supercomputers. She writes, "Over the
past year, the Trump administration has
increasingly embraced the AI industry.
In December, Trump signed an executive
order to bar states and local
governments from enacting their own AI
regulations. Soon after he signed the
order, his family's company, Trump Media
and Technology, announced a $6 billion
merger with a firm aiming to build the
world's first viable nuclear fusion
plant to power AI projects. Karen How is
a former reporter at the Wall Street
Journal and MIT Technology Review where
she became the first journalist to
profile open AI. Democracy Now's Juan
Gonzalez and I spoke to her in May. The
National Book Critic Circle recently
named her book The Empire of AI: Dreams
and Nightmares and Sam Alman's Open AI
as a finalist for best non-fiction book
of 2025.
I began by asking Karen How to explain
just what artificial intelligence is. So
AI is a collection of many different
technologies but most people were
introduced to it through chatbt and what
I argue in the book and what the title
refers to empire of AI it's actually a
critique of the specific trajectory of
AI development that led us to chatbt and
has continued since chatbt and that is
specifically Silicon Valley's scale at
all costs approach to AI development AI
models in modern day they are trained on
data they need computers to train them
on that data. But what Silicon Valley
did and what OpenAI did in the last few
years is they started blowing up the
amount of data and the the size of the
computers that need to do this training.
So we are talking about the full English
language internet being fed into these
models, books, scientific articles, all
of the intellectual property that is
being created and also massive
supercomputers that run tens of
thousands even hundreds of thousands of
computer chips that are the size of
dozens maybe hundreds of football fields
and use practically the entire energy
demands of cities now. So this is an
extraordinary um type of AI development
that is causing a lot of social, labor
and environmental harms and that is
ultimately why I evoke this analogy to
empire.
>> And Karen, could you talk some more
about not only the energy requirements
but the water requirements of these huge
data centers that are essence in essence
the backbone of of this uh widening uh
industry?
>> Absolutely. I'll give you two stats on
both the energy and the water. When
talking about the energy demand,
McKenzie recently came out with a report
that said in the next 5 years based on
the current pace of AI computational
infrastructure expansion, we would need
to put as much energy on the global grid
as what is consumed by two to six times
the energy consumed annually by the
state of California. And that will
mostly be serviced by fossil fuels.
We're already seeing reporting of uh
coal plants with their lives being
extended. They were supposed to retire
but now they cannot to support this data
center development. We are seeing
methane gas turbines, unlicensed ones
being popped up to uh service these data
centers as well. From a freshwater
perspective, these data centers need to
be trained on freshwater. They cannot be
trained on any other type of water
because it can corrode the equipment. It
can lead to bacterial growth and most of
the time it actually taps directly into
a public drinking water supply because
that is the infrastructure that has been
laid to deliver this clean fresh water
to different businesses to different
homes. And Bloomberg recently had an
analysis where they looked at the
expansion of these data centers around
the world and 2thirds of them are being
placed in water scarce areas. So they're
being placed in communities that do not
have access to fresh water. So it's not
just the total amount of fresh water
that we need to be concerned about, but
actually the distribution of this
infrastructure around the world.
And most people are familiar with chat
GPT the consumer aspect of AI but what
about the military uh aspect of AI where
in essence uh we're finding Silicon
Valley companies becoming the next
generation of defense contractors.
>> One of the reasons why OpenAI and many
other companies are turning to the
defense industry is because they have
spent an extraordinary amount of money
in developing these technologies.
They're spending hundreds of billions to
train these models and they need to
recoup those costs and there are only so
many industries and so many places that
have that size of a paycheck to pay. And
so that's why we're seeing a cozying up
to the defense industry. We're also
seeing Silicon Valley use the US
government in their empire building
ambitions. You could argue that the US
government is also trying to use Silicon
Valley vice versa in their empire
building ambitions. Um but certainly
these technologies are not they are not
designed to be used in a sensitive
military context. And so the the
aggressive push of these companies to
try and get those defense contracts and
integrate their technologies more and
more to the into the infrastructure of
the military is really alarming. I
wanted to go to the countries you went
to or the stories you covered because I
mean this is amazing the depth of your
reporting from Kenya to Uruguay to
Chile. Um you were talking about the use
of water and I also want to ask you
about nuclear power. Uh but in Chile um
what is happening there around these
data centers and the water they would
use and the resistance to that.
>> Yeah. So Chile has an interesting
history in that it's been under it was
under a dictatorship for a very long
time. And so during that time, most
public resources were privatized,
including water. But because of an
anomaly, there's one community in the
greater Santiago metropolitan region
that actually still has access to a
public freshwater resource that services
both that community as well as the rest
of the country in emergency situations.
That is the exact community that Google
chose to try to put a data center in
>> and it would be free
>> and it, you know, I have no idea. That
is a great question. But what the
community told me was they weren't even
paying taxes for this because they they
believed based on reading the
documentation that the taxes that Google
was paying was in fact to where they had
registered their offices, their
administrative offices, not where they
were putting down the data center. So
they were not seeing any benefit from
this data center directly to that
community and they were seeing no checks
placed on the fresh water that this data
center would have been allowed to
extract. And so these activists said,
"Wait a minute, absolutely not. We're
not going to allow this data center to
come in unless they give us a legitimate
reason for why it benefits us." And so
they started doing boots on the ground
activism, pushing back, knocking on
every single one of their neighbors
doors, handing out flyers to the
community, telling them this company is
taking our freshwater resources without
giving us anything in return. And so
they escalated so dramatically that it
escalated to Google Chile. It escalated
to Google Mountain View, which by the
way then sent representatives to Chile
that only spoke English.
But then it eventually escalated to the
Chilean government. And the Chilean
government now has roundts where they
ask these community residents and the
company representatives and
representatives from the government to
come together to actually discuss how to
make data center development more
beneficial to the community. The
activists say it is the fight is not
over. Just because they've been invited
to the table doesn't mean that
everything is suddenly better. They need
to stay vigilant. They need to continue
scrutinizing these projects. But thus
far they've been able to block this
project for four to five years and have
gained that seat at the table.
>> And how is it that these uh western
companies in essence are exploiting
labor in the global south? You go into
something called data annotation firms.
What what are those?
>> Yeah. So because AI modern day AI
systems are trained on massive amounts
of data and they're sc that's scraped
from the internet, you can't actually
pump that data directly into your AI
model because there are a lot of things
within within that data. It's heavily
polluted. It needs to be cleaned. It
needs to be annotated. So this is where
data annotation firms come in. These are
middleman firms that hire contract labor
to provide to these AI companies to do
that kind of data preparation. And open
AI when it was starting to think about
commercializing its products and
thinking about let's put text generation
machines that can spew any kind of text
into the hands of millions of users.
They realized they needed to have some
kind of content moderation. They needed
to develop a filter that would wrap
around these models and prevent these
models from actually spewing racist,
hateful, and harmful speech to users
that would not make a very good
commercially viable product. And so they
contracted these middleman firms in
Kenya where the Kenyan workers had to
read through reams of the worst text on
the internet as well as AI generated
text where open AI was prompting its own
AI models to imagine the worst text on
the internet and then telling these
Kenyan workers to detail to categorize
them in detailed taxonomies of is this
sexual content, is this violent content,
how graphic is that violent content in
order to teach its filter all the
different categories of content it had
to block. And this is incredibly
uncommon form of labor. There are lots
of other different types of contract
labor that they use. But these workers,
they're paid a few bucks an hour, if at
all. And just like the era of social
media, these content moderators are left
very deeply psychologically traumatized.
And ultimately, there is no real
philosophy behind why these workers are
paid a couple bucks an hour and have
their lives destroyed. And why AI
researchers who also contribute to these
models are paid million-doll
compensation packages simply because
they sit in Silicon Valley in OpenAI's
offices. That is the logic of Empire.
And that hearkens back to my title,
Empire of AI.
>> So, let's go back to your title, Empire
of AI. the subtitle dreams and
nightmares in Sam Alman's Open AI. So
tell us the story of Sam Alman and what
Open AI is all about right through to
the deal he just made in the Gulf when
President Trump uh Sam Alman and Elon
Musk were there. Alman is very much a
product of Silicon Valley. His career
was first as a founder of a startup and
then as the president of Y Combinator,
which is one of the most famous startup
accelerators in Silicon Valley, and then
the CEO of OpenAI. And there's no
coincidence that OpenAI ended up
introducing the world to the scale at
all cost approach to AI development
because that is the way that Silicon
Valley has operated in the entire time
that Altman came up in it. And so he is
a very strategic person. He is
incredibly good at telling stories about
the future and painting these sweeping
visions that investors and employees
want to be a part of. And so early on at
YC, he identified that AI would be one
of the trends that could take off. And
he was trying to build a portfolio of
different investments and different
initiatives to place himself in the
center of various different trends
depending on which one took off. He was
investing in quantum computing. He was
investing in nuclear fusion. He was
investing in self-driving cars. And he
was developing a fundamental AI research
lab. Ultimately, the AI research lab was
the ones that started accelerating
really quickly. So he makes himself the
CEO of that company. Um and and
originally he started it as a nonprofit
to try and position it as a counter to
forprofit driven incentives in Silicon
Valley. But within one and a half years,
OpenAI's executives identified that if
they wanted to be the lead in this
space, they had to go for this scale at
all cost approach and had to should be
in quotes. They thought that they had to
do this. There are actually many other
ways to develop AI and to have progress
in AI that does not take this approach.
But once they decided that, they
realized the bottleneck was capital. It
just so happens Sam Alman is a once in a
generation fundraising talent. He
created this new structure nesting a
for-profit arm within the nonprofit to
become this fundraising vehicle for the
tens of billions and ultimately hundreds
of billions that they needed to pursue
the approach that they decided on. And
that is how we ultimately get to present
day OpenAI, which is one of the most
capitalistic companies in the history of
Silicon Valley, continuing to raise
hundreds of billions and and Altman has
joked even trillions to produce a
technology that ultimately has a
middling economic impact thus far. We'll
return to our conversation in a minute
with Karen How, author of the new book
Empire of AI: Dreams and Nightmares in
Sam Alman's Open AI. Stay with us.
This is Democracy Now! democracynow.org.
I'm Amy Goodman. In this holiday
special, we continue with the journalist
Karen How, author of the new book Empire
of AI: Dreams and Nightmares, and Sam
Alman's Open AI. Karen came into our
studio in May when she discussed how AI
will impact workers.
One of the things that we have seen is
this technology is already having a huge
impact on jobs.
Not necessarily because the technology
itself is really capable of replacing
jobs, but it is perceived as capable
enough that executives are laying off
workers. And we need more some kind of
more guard rails to actually prevent
these companies from continuing to try
and develop labor automating
technologies and try to shift them to
producing labor assistive technologies.
What do you mean?
>> So, open AI, their definition of what
they call artificial general
intelligence is highly autonomous
systems that outperform humans in most
economically valuable work. So, they
explicitly state that they are trying to
automate jobs away. I mean, what are
what is economically valuable work? But
the things that people do to get paid.
Um but there's this really great book
called Power in Progress by MIT
economists Jeron Austin and Simon
Johnson who mention that technology
development all technology revolutions
they take a labor automating approach
not because of inevitability but because
the people at the top choose to automate
those jobs away. They choose to design
the technology so that they can sell it
to executives and say you can shrink
your costs by laying off all these
workers and using our AI services
instead. But in the past, we've seen
studies that for example suggest that if
you develop an AI tool that a doctor
uses rather than replacing the doctor,
you will actually get better health care
for patients. you will get better di
cancer diagnoses. If you develop an AI
tool that teachers can use rather than
just an AI tutor that replaces the
teacher, your kids will get better
educational outcomes. And so that's what
I mean by labor assistive than labor
>> and explain uh what you mean because I
think a lot of people don't even
understand artificial intelligence. And
when you say replace the doctor, what
are you talking about?
>> Right. So these companies they try to
develop a technology that they position
as an everything machine that can do
anything. Um and so they will try to say
you can use this you can talk to chatbt
for therapy. No, you cannot. Chat GBT is
not a licensed therapist. And in fact,
these models actually spew lots of
medical misinformation. And there have
been lots of um examples of actually
users being psychologically harmed by
the model because the model will
continue to reinforce um selfharming
behaviors. And we've even had cases
where uh children who speak to chatbots
and develop huge emotional relationships
with these chatbots have actually killed
themselves after using these chatbot
systems. Um but that's what I mean when
these companies are trying to develop
labor automating tools. They're
positioning it as you can now hire this
tool instead of hire a worker. I mean,
most recently, Sam Alman was speaking at
a conference and said, "We originally
said that these models were junior level
partners at a law firm, and now we think
that they can really be more senior
colleagues at a law firm." What he's
saying is don't hire the junior level
partners, don't hire the senior
colleagues, and just use our AI models.
And we are already seeing the career
ladder breaking because many different
white collar job uh white collar service
industries as well as other industries
are becoming convinced that they do not
need to hire interns. They do not need
to hire entry-level positions that they
just need these AI models and new
college graduates are struggling now to
find job opportunities to help them get
a foothold into these industries. So,
you've talked about Sam Alman, and in
part one, we touched on uh who he is,
but I'd like you to go more deeply into
what uh who Sam Alman is, how he
exploded onto the um US scene,
testifying before Congress, actually
warning about the dangers of AI. So,
that really protected him in a way.
>> Um people seeing him as a prophet.
That's a P O P. But now, we can talk
about the other kind of prophet, P O Fit
T.
um and how open AI was formed. How is
open AI different from AI?
OpenAI is a com I mean it was originally
founded as a nonprofit as I mentioned
and Alman specifically when he was
thinking about how do I make a
fundamental AI research lab that is
going to make a big splash he chose to
make it a nonprofit because he
identified that if he could not compete
on capital and he was relatively late to
the game Google already had a monopoly
on a lot of top AI research talent at
the time if he could not compete on
capital and he could not compete um in
in terms of being a first mover he
needed some other kind of ingredient
there to really recruit talent recruit
um public goodwill and establish a name
for open AAI so he identified a mission
he identified let me make this a
nonprofit and let me give it a really
compelling mission so the mission of
openai is to ensure artificial general
intelligence benefits all of humanity
And one of the quotes that I open my
book with is this quote that Sam Alman
cited himself in 2013 um in his blog. He
was an avid blogger back in the day
talking about his learnings on business
and strategy and Silicon Valley startup
life. And the quote is successful people
built companies, more successful people
build countries. The most successful
people build religions. And then he
reflects on that quote in his blog
saying, "It appears to me that the best
way to build a religion is actually to
build a company."
>> And so talk about how Alman was then
forced out of the company and then came
back. And also I just found it so
fascinating that you were able to speak
with so many Open AI workers. You
thought there was a kind of total ban on
you.
>> Yes. Yeah. Exactly. So I was the first
journalist to profile OpenAI. Um, I
embedded within the company for 3 days
in 2019 and then my profile published in
2020 for MIT technology review and at
the time I identified in the profile
this tension that I was seeing where it
was a nonprofit by name but behind the
scenes a lot of the public values that
they exposed were actually the opposite
of how they operated. So they espoused
transparency but they were highly
secretive. They espoused
collaboriveness. They were highly
competitive. and they espoused that they
had no commercial intent, but in fact it
seemed like they had just gotten a $1
billion investment from Microsoft. It
seems like they were rapidly going to
develop commercial intent. And so I
wrote that into the profile and OpenAI
was deeply unhappy about it and they
would not refuse to talk to me for 3
years. But when I started working on the
book, when I started reaching out to
employees, current and former, I
discovered that many employees actually
really liked the profile and they
specifically wanted to talk to me
because they thought that I would do
justice to the truth of what had
actually happened within the company and
be able to discover behind what the
executives mythologized and narrativized
about this technology [clears throat]
and about the course of this company. I
would be able to actually get beneath
that to the real heart of the matter.
And so um one of the things that you
really have to understand about AI
development today is that there are what
I call quasi religious movements that
have developed within Silicon Valley.
The concept of artificial general
intelligence is not one that's
scientifically grounded. It is this idea
that we can fundamentally recreate human
intelligence in computers. And this idea
has been around for actually a really
long time. The field of AI was founded
all the way back in the 1950s and that
was the original intent of the field.
How do we recreate intelligence in
computers? Can machines think? That was
the famous question that British
mathematician Alan Turing asked. But we
to this day do not have scientific
consensus around even what human
intelligence is. And so to peg an entire
research field and a technology to the
basis of human intelligence is a very
tricky endeavor because there are no
good metrics to assess have we actually
gotten there yet and there's no
blueprint to say what should AI look
like and how should it work and
ultimately who should it serve. And so
when OpenAI took up this mission of
artificial general intelligence, they
were able to essentially shape and mold
what they wanted this technology to be
based on what is most convenient for
them. But when they identified it, it
was at a time when scientists really
looked down on this term even AGI. And
so they absorbed just a small group of
self-identified AGI believers. This is
why I call it quasi religious because
there's no scientific evidence that we
can actually develop AGI. The people who
are strongly con have this strong
conviction that they will do it and that
it's going to happen soon. It is just
purely based on belief and they talk
about it as a belief too. But there are
two factions within this belief system
of the AGI religion. There are people
who think AGI is going to bring us to
utopia and there are people who think
AGI is going to destroy all of humanity.
Both of them believe that it is
possible. It's coming soon. And
therefore they conclude that they need
to be the ones to control the technology
and not democratize it. And this is
ultimately what leads to your question
of what happened when Sam Alman was
fired and rehired through the history of
OpenAI. There's been a lot of clashing
between the boomers and doomers about
who should actually
>> the boomers and doomers.
>> The boomers and the doomers. [laughter]
>> Those that say it'll bring us the
apocalypse. topia boomers and those that
say it'll destroy humanity. The doomers
and they have clashed relentlessly and
aggressively about how quickly to build
the technology, how quickly to release
the technology and ultimately Altman is
one that he is really good at saying to
people what they need to hear and he
will say different things to different
people if he thinks they need to hear
different things. So when I asked
boomers, is Altman a boomer? They said
yes. When I asked doomers, is Altman a
doomer? They said yes. And I want to
take this up until today to um in
January, the Trump administration
announcing the Stargate project, a $500
billion project to boost AI
infrastructure in the United States.
This is Open AI Sam Alman speaking
alongside President Trump.
I think this will be the most important
project of this era and as Masa said for
AGI to get built here to create hundreds
of thousands of jobs to create a new
industry centered here. Uh we wouldn't
be able to do this without you Mr.
President.
>> He also there referred to AGI um uh
artificial general intelligence. Explain
what happened here and what this is and
has it actually happened. So Altman
before Trump was elected
um he already was sensing through
observation that it was possible that
the administration would shift and that
he would need to start politicking quite
heavily to ingruiate himself to a new
administration.
Alman is very strategic. Um he was under
a lot of pressure at the time as well
because his original co-founder Elon
Musk now has great beef with him. Uh
Musk feels like Alman used his name and
his money to set up OpenAI and then he
got nothing in return. So Musk had been
suing him, still suing him and suddenly
became first buddy of the Trump
administration. So Altman basically
cleverly orchestrated
a um this announcement where by the way
the the announcement is quite strange
because the Trump President Trump is not
it's not the US government giving $500
billion. It's private investment coming
into the US um from places like Soft
Bank
>> which is
>> uh which is one of the largest
investment funds um run by Masay Yoshi
Son a Japanese businessman who made a
lot of his wealth from the previous tech
era. So, so it's not even the US
government that's that's providing this
money.
>> And take that right through to now that
Gulf trip that um Elon Musk was on, but
so was Sam Alman to the fury of Elon
Musk and then a deal was sealed in Abu
Dhabi.
>> Yeah.
>> It didn't include Elon Musk but was
about open AI.
>> Exactly. So Altman has continued to try
and use the US government as a way to to
get access to more places and uh more
powerful spaces to build out this
empire. And one of the one of the things
because OpenAI's computational
infrastructure needs are so aggressive.
You know, I had an OpenAI employee tell
me we're running out of land and power.
So they are running out of resources in
the US which is why they're trying to
get access to land and energy in other
places. The Middle East has a lot of
land and has a lot of energy and they're
willing to strike deals and that is why
Altman was part of that trip looking to
strike a deal and what they the deal
that they struck was to build a massive
data center or multiple data centers in
the Middle East using their land and
their energy. But one of the things that
OpenAI has recently rolled out, they
call it the OpenAI for countries program
and it is this idea that they want to
install OpenAI hardware and software in
places around the world and explicitly
says we want to build democratic AI
rails.
We want to install our hardware and
software as a foundation of democratic
AI globally so that we can stop China
from installing authoritarian AI
globally. But the thing that he does not
acknowledge is that there is nothing
democratic about what he's doing. You
know, the Atlantic executive editor says
we need to call these companies for what
they are. They are techno
authoritarians. They do not ask the
public for any perspective on how they
develop the technology, what data they
train the technology on, where they
develop these data centers. In fact,
these data centers are often developed
in the cover of night um under shell
companies like Meta recently entered New
Mexico under the Shell company named
Greater Kudu LLC.
>> Greater Kudu.
>> Greater Kudu LLC. And once the deal was
actually closed and the residents
couldn't do anything about anymore,
that's when it was revealed, surprise,
we're Meta and you're going to get a
data center that drinks all of your
fresh water.
>> And then there was this whole
controversy in Memphis around a data
center.
>> Yes. So that is the data center that
Elon Musk is building. So meanwhile,
Musk is saying Alman is terrible.
Everyone should use my AI. And of
course, his AI is also being developed
using the same environmental and public
health costs. So he built this massive
supercomputer called Colossus in
Memphis, Tennessee that's training
Grock, the chatbot that people can
access through X and that is being
powered by
around 35 unlicensed methane gas
turbines that are pumping thousands of
tons of toxic air pollutants into the
greater Memphis community. And that
community has long suffered a lack of
access to clean air, a fundamental human
right.
>> So I want to go to interestingly Sam
Alman testifying in front of Congress
about solutions to the high energy
consumption of artificial intelligence.
>> In the short term, I think this probably
looks like more natural gas. Um although
there are some applications where I
think solar can really help. In the
medium-term, I hope it's advanced
nuclear uh fish and fusion. More energy
is important well beyond AI.
>> So that's open AI's Sam Alman. This is
testifying before the Senate and talking
about everything from uh solar to
nuclear power. Something that was fought
in the United States by environmental
activists for decades. So you have these
huge old uh nuclear power plants, but
many say you can't make them safe no
matter how small. and smart you make
them.
>> This is one of the things of the many
things that I'm concerned about with the
current trajectory of AI development.
This is a second order tertiary order
effect is that because these companies
are trying to claim that the AI
development approach they took doesn't
have climate harms. They are explicitly
evoking nuclear again and again and
again as nuclear will solve the problem.
And it has been effective. I have talked
with certain AI researchers who thought
the problem was solved because of
nuclear and in order to try and actually
build more and more nuclear plants, they
are lobbying governments to try and
unwind the regulatory structure around
nuclear power plant building. I mean
this is this is like crazy on so many
levels that they're not just trying to
develop these the AI technology
recklessly. They are also trying to lay
down infrastructure and nuclear
infrastructure in this move fast break
things ideology. But for those who um
are environmentalists and have long
opposed nuclear will they be sucked in
by the solar alternative? But that exact
so data centers have to run 247. So they
cannot actually run on just renewables.
That is why the companies keep trying to
evoke nuclear as the solve all but solar
does not actually work when we do not
have sufficient enough energy storage
solutions for that 24/7 operation. We'll
return to our conversation in a minute
with Karen How, author of the new book
Empire of AI: Dreams and Nightmares in
Sam Alman's Open AI. Stay with us.
This is Democracy Now! Democracynow.org.
I'm Amy Goodman. In this holiday
special, we're speaking with the
journalist Karen How, author of the new
book Empire of AI: Dreams and Nightmares
in Sam Alman's Open AI. She came into
our studio in May. She lives in Hong
Kong. I asked her to talk about what's
happening in China around artificial
intelligence.
>> China and the US are the largest hubs
for AI research. They are the largest
concentration of AI research talent
globally. Um, China other than Silicon
Valley, China really is the only other
rival in terms of talent density and the
amount of capital investment and the
amount of infrastructure that is going
into AI development. In the last few
years, what we have seen is the US
government has been aggressively trying
to stay number one and one of the
mechanisms that they have used is export
controls. A key input into these AI
models is the computational
infrastructure and the computer chips
for installing into the data centers for
training these models. And these
computer chips are the in order to
develop the AI models. Companies are
using the most bleeding edge computer
chip technology. It's like the every two
years a new chip comes out and they
immediately start using that to train
the next generation of AI models. Those
computer chips are designed by American
companies, the most prominent one being
Nvidia in California. And so the US
government has been trying to use export
controls to prevent Chinese companies
from getting access to the most cutting
edge computer chips. That has all been
under the recommendation of Silicon
Valley saying this is the way to prevent
China from being number one. and like
put export controls on them and don't
regulate us at all so we can stay number
one and they will fall behind. What has
happened instead
is because there is a strong base of
talent of AI research talent in China
under the constraints of fewer
computational resources, Chinese
companies have actually been able to
innovate and develop the same level of
AI model capabilities as American
companies with two orders of magnitude
less computational resources, less
energy, less data. So, I'm talking
specifically about um the Chinese
company Highfire, which developed this
model called Deep Seek earlier this year
that briefly tanked the global economy
because the company said that their
their um training this one AI model cost
around $6 million when OpenAI was
training models that cost hundreds of
millions if not over tens of billions of
dollars. And that delta demonstrated to
people that this what Silicon Valley has
tried to convince everyone for the last
few years that this is the only path to
getting more AI capabilities is totally
false and actually the techniques that
chi the Chinese company was using were
ones that existed in the literature and
just had to be assembled. They used a
lot of engineering sophistication to do
that, but they weren't actually using
fundamentally new techniques. They were
ones that actually already existed.
>> So explain it further because I think a
lot of people just can't get their minds
around this. How do you do this
training?
>> So there's software called neural
networks which is essentially a massive
statistical engine. is doing lots and
lots of sophisticated statistical
computation to try and ascertain what
kinds of patterns exist in data sets. So
typically in in the past before we got
to large language models it would be
doing something like um looking at MRI
scans and checking the patterns of what
what does cancer look like in an MRI
scan. Um now with GBT what it's looking
at is what are the patterns of the
English language? what is the syntax,
the structure, figures of speech that
are typically used and then it uses
those patterns to construct new
sentences. That's how generative AI
works. And the reason why it's so
computationally expensive is because
it's crunching the numbers for those
patterns. And the more data you feed in,
the more it has to crunch. And so it we
used to train these AI models on you
know a powerful laptop like maybe one
computer chip maybe the richest labs
academic labs like MIT they would be uh
training on a couple or a dozen computer
chips and companies like Google they
would be training maybe on a couple
hundred computer chips. We are now
talking about hundreds of thousands of
computer chips training a single model.
Um and that is the you know that is what
open AI says is necessary to build these
technologies and that is what deepseek
proved wrong. So, let me ask you
something, Karen. uh the latest news um
as you're traveling in the United States
before you go back to Hong Kong uh of
Trump's attack on academia, how this
fits in. Um how could Trump's attack on
international students specifically
targeting the what more than 250,000 a
quarter of a million Chinese students
and revoking their visas impact the
future of the AI industry. But not just
Chinese students because what's going on
here now is terrifying students around
the world and because labs are shutting
down in all kinds of ways here uh US
students as well uh deciding to go
abroad.
This is just the latest action that the
US government has taken over the last
few years to really alienate a key
talent pool for US innovation.
Originally, there were more Chinese
researchers working in the US
contributing to US AI than there were in
China because [snorts] just a few years
ago, Chinese researchers aspired to work
for American companies. They wanted to
move to the US. They wanted to
contribute to the US economy. They
didn't want to go back to their home
country. But because of what was called
the China Initiative, which was the a
first Trump era initiative to try and
criminalize Chinese academics or
ethnically Chinese academics, some of
whom were actually Americans um based on
just paperwork errors. They would accuse
them of being spies. That was one of the
first actions. Then of course the
pandemic happened and the USChina trade
escalations started amplifying
anti-Chinese rhetoric. All of these led
and now with the potential ban on
international students. All of these
have led more and more Chinese
researchers to just opt for staying at
home and contributing to the Chinese AI
ecosystem. And this was a prerequisite
to High-fly pulling off Deepseek. If
there had not been that concentration
and buildup of AI talent in China, they
probably would have had a much harder
time innovating around circumventing
these export controls that the US
government was imposing on them. But
because they now have a high
concentration of top talent, some of the
top talent globally,
when those restrictions were imposed,
they were able to innovate around them.
So Deepseek is literally a product of
this continuation of that alienation and
with the US continuing to take this
stance, it is just going to get worse.
And as you mentioned, it's not just
Chinese researchers. I literally just
talked to a friend in academia that said
she's considering going to Europe now
because she just cannot survive without
that public funding. And Europe European
countries are seeing a critical
opportunity offering milliondoll
packages. Come here, we'll give you a
lab. We'll give you millions of dollars
of funding. I mean this is the fastest
way to brain drain this country.
>> I mean what many are saying US's brain
drain is their brain gain. Yes.
>> And this also reminds us of history. You
have the Chinese rocket scientist Chen
Shuen who in the 1950s was inexplicably
held under house arrest for years and
then Eisenhower has him deported to
China. He becomes the father of rocket
science and uh China's entry into space.
And he said he would never again step
foot into the United States even though
originally that was the only place he
wanted to live.
>> Yes. And there was a I believe a
government official, a US government
official who said that was the dumbest
mistake the US ever made.
>> Um you we talk about the brain drain and
the brain gain. Okay. Again, uh some
more rhyming, the doomers and the
boomers. Um, I want to talk about what
an AI apocalypse looks like, meaning how
it brings us to apocalypse, but also um
how uh people say it could lead us to a
utopia. What are the two tracks
trajectories?
>> It's a great question and I ask boomers
and doomers this all the time. Can you
articulate to me exactly how we get
there? And the issue is that they
cannot. And this is why I call it quasi
religious. It really is based on belief.
I mean, I was talking with one
researcher who identified as a boomer.
And I said, you know, he his his eyes
were wide and he he really lit up
saying, you know, once we get to AGI,
game over. Everything becomes perfect.
And I asked him, I was like, can you
explain to me how does AGI feed people
that haven't don't have food on the
table right now? And he was like, "Oh,
you're talking about like the floor
floor and how to elevate their quality
of life." And I was like, "Yes, because
they are also part of all of humanity."
And he was like, "I'm not really sure
how that would happen, but I think it
could it could help the middle class get
more economic opportunity." And I was
like, "Okay, but how does that happen as
well?" And he was like, "Well, once
these come once we have AGI and it can
just create trillions of dollars of
economic value, we can just give them
cash payouts." And I was like, who's
giving them cash payouts? What
institutions are giving them? You know,
like it it doesn't when you actually
test their logic, it doesn't really
hold. And with the doomers, I mean, it's
the same thing. like their belief is
ultimately
what I realized when reporting on the
book is they believe AGI is possible
because of their belief of how the human
brain works. They believe human
intelligence is inherently fully
computational. So if you have enough
data and you have enough computational
resources, you will inevitably be able
to recreate human intelligence. It's
just a matter of time. And to them, the
reason why there would that would lead
to an apocalyptic scenario is humans, we
learn and improve our intelligence
through communication. And communication
is inefficient. We miscommunicate all
the time. And so for AI intelligences,
they would be able to rapidly get
smarter and smarter and smarter by
having perfect communication with one
another as digital intelligences. And so
many of these people who selfidentify as
doomers say there has never been in the
history of the the universe a species
that was superior to another species a a
species that was able to rule over um a
more superior species. So they think
that ultimately AI will evolve into a
higher species and then start ruling us
and then maybe decide to get rid of us
altogether. I'm wondering if you can
talk about any model of a country, not a
company,
>> that is pioneering a way of
democratically controlled artificial
intelligence.
>> I don't think it's actively happening
right now.
The EU has had the EU AI act, which is
their major piece of legislation trying
to develop a riskbased, rightsbased
framework for governing AI um
deployment.
But
to me, one of the keys of democratic AI
governance is also democratically
developing AI. And I don't think any
country is really doing that. And what I
mean by that is there are AI has a
supply chain. It needs data. It needs
land. It needs energy. It needs water.
And it also needs spaces in which these
companies need access to to then deploy
their technology. Schools, hospitals,
government agencies. Silicon Valley has
done a really good job over the last
decade of making people feel that their
collectively owned resources are Silicon
Valleys. You know, I have I talk with
friends all the time who say, "We don't
have data privacy anymore." So, like,
what's more what's what is more data to
these companies? Like, I'm fine just
giving them all of my data. But that
data is yours. You know, that
intellectual property is the writers and
artists intellectual property. That land
is a community's land. Those schools are
the students and teachers schools. The
hospitals are the doctors and nurses and
patients hospitals. These are all sites
of democratic contestation in the
deployment in the development and the
deployment of AI. And just like those
Chilean water activists that we talked
about who aggressively understood that
that fresh water was theirs and they
were not willing to give it up unless
they got some kind of mutually
beneficial agreement for it. We need to
have that spirit in protecting
our data, our land, our water, and our
schools so that companies inevitably
will have to adjust their approach
because they will no longer get access
to the resources they need or the spaces
that they need to deploy in. In 2022,
Karen, you wrote a piece for MIT
Technology Review headlined a new vision
of artificial intelligence for the
people. In a remote rural town in New
Zealand, an indigenous couple is
challenging what AI could be and who it
should serve. Who are they? This was a
wonderful story that I did where the
couple um they run to media. It's a
nonprofit MAI radio station in New
Zealand. And the Maui people have
suffered a lot of the same um challenges
as many indigenous peoples around the
world. The history of colonization led
them to rapidly lose their language and
there are very few Mauy speakers in the
world anymore. And so in the last few
years there's been an attempt to revive
the language and the New Zealand
government has tried to repent by by
trying to encourage that the revival of
that language. But this nonprofit radio
station, they had all this wonderful
archival material, archival audio of
their ancestors speaking the Mai
language that they wanted to provide to
Maui speakers, ma Mai learners around
the world as an educational resource.
The problem is in order to do that they
needed to transcribe the audio so that
Mai learners could actually listen, see
what was being said, click on the words,
understand the translation and actually
turn it into an active learning tool.
But there were so few Maui speakers that
can speak at that advanced level that
they realized they had to turn to AI.
And this is a key part of my book's
argument is I'm not critiquing all AI
development. I'm specifically critiquing
the scale at all cost approach that
Silicon Valley has taken. But there are
many different kinds of beneficial AI
models, including what they ended up
doing. So they took a fundamentally
different approach. First and foremost,
they asked their community, do we want
this AI tool? Once the community said
yes, then they moved to the next step of
asking people to fully consent to
donating data for the training of this
tool. They explained to the community
what this data was for, how it would be
used, how they would then guard that
data and make sure that it wasn't used
for other purposes.
They collected around a couple hundred
hours of audio data in just a few days
because the community rallied support
around this project and only a couple
hundred hours was enough to create a
performant speech recognition model
which is crazy when you think about the
scales of data that these Silicon Valley
companies require. And that is once
again a lesson that can be learned is
actually there's plenty of research that
shows when you have highly curated small
data sets, you can actually create very
powerful AI models and then once they
had that tool, they were able to do
exactly what they wanted to open source
and resour uh open source this
educational resource to their community.
And so my vision for AI development in
the future is to have more small
taskspecific AI models that are not
trained on vast polluted data sets but
small curated data sets and therefore
only need small amounts of computational
power and can be deployed in challenges
that we actually need to tackle for
humanity.
mitigating climate change by integrating
more renewable energy into the grid,
improving health care, by doing more
drug discovery.
>> So, as we finally do wrap up, what you
were most shocked by, you've been doing
uh this journalism, this research for
years, what you were most shocked by in
writing Empire of AI.
I originally thought that I was going to
write a book focused on vertical harms
of the AI supply chain. Here's how labor
exploitation happens in the AI industry.
Here's how the environmental harms are
arising out of the AI industry. And at
the end of my reporting, I realized that
there is a horizontal harm that's
happening here. Every single community
that I spoke to, whether it was artists
having their intellectual property taken
or Chilean water water activists having
their fresh water taken, they all said
that when they encountered the empire,
they initially felt exactly the same
way. A complete loss of agency to
self-determine their future. And that is
when I realized the horizontal harm here
is AI is threatening democracy. If the
majority of the world is going to feel
this loss of agency over
self-determining their future, democracy
cannot survive and again specifically
Silicon Valley's approach scale at all
costs AI development.
>> But you also chronicle the resistance.
You talk about how the Chilean water
actors felt at first, how the artists
feel at first. So talk about the
strategies that these people have
employed and if they've been effective.
>> So the amazing thing is that there has
since been so much push back. The
artists have then said wait a minute we
can sue these companies. The Chilean
water activists said wait a minute we
can fight back and protect these water
resources. The Kenyan workers that I
spoke to who are contracted by OpenAI
they said we can unionize and escalate
our story to international media
attention. And so even in these even
when I thought that these communities
you could argue are the most vulnerable
in the world have the least amount of
agency, they were the ones that
remembered that they do have agency and
that they can seize that agency and
fight back. And I think it it was it was
remarkably heartening to encounter those
people to remind me that actually the
first step to reclaiming democracy is
remembering that no one can take your
agency away.
>> Karen How, author of the new book Empire
of AI: Dreams and Nightmares and Sam
Alman's Open AI. Karen How is a former
reporter at the Wall Street Journal and
MIT Technology Review. And that does it
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