This is democracyow [music]democracynow.orgthe War and Peace Report. I'm AmyGoodman. The Empire of AI, that's the
name of a new book by journalist KarenHow, who's been closely reporting on therise of the artificial intelligence
industry with a focus on Sam Alman'sOpen AI. That's the company behind ChatGPT. Karen how compares the actions of
the AI industry to those of colonialpowers of the past. She writes, quote,"The empires of AI are not engaged in
the same overt violence and brutalitythat marked this history, but they tooseize and extract precious resources to
feed their vision of artificialintelligence. the work of artists andwriters, the data of countlessindividuals posting about their
experiences and observations online, theland, energy, and water required tohouse and run massive data centers and
supercomputers. She writes, "Over thepast year, the Trump administration hasincreasingly embraced the AI industry.
In December, Trump signed an executiveorder to bar states and localgovernments from enacting their own AI
regulations. Soon after he signed theorder, his family's company, Trump Mediand Technology, announced a $6 billion
merger with a firm aiming to build theworld's first viable nuclear fusionplant to power AI projects. Karen How is
a former reporter at the Wall StreetJournal and MIT Technology Review whereshe became the first journalist to
profile open AI. Democracy Now's JuanGonzalez and I spoke to her in May. TheNational Book Critic Circle recently
named her book The Empire of AI: Dreamsand Nightmares and Sam Alman's Open AIas a finalist for best non-fiction book
of 2025.I began by asking Karen How to explainjust what artificial intelligence is. SoAI is a collection of many different
echnologies but most people wereintroduced to it through chatbt and whatI argue in the book and what the title
refers to empire of AI it's actually acritique of the specific trajectory ofAI development that led us to chatbt and
has continued since chatbt and that ispecifically Silicon Valley's scale atall costs approach to AI development AI
models in modern day they are trained ondata they need computers to train themon that data. But what Silicon Valley
did and what OpenAI did in the last fewyears is they started blowing up theamount of data and the the size of the
computers that need to do this training.So we are talking about the full Englishlanguage internet being fed into these
models, books, scientific articles, allof the intellectual property that isbeing created and also massive
supercomputers that run tens ofthousands even hundreds of thousands ofcomputer chips that are the size of
dozens maybe hundreds of football fieldsand use practically the entire energydemands of cities now. So this is an
extraordinary um type of AI developmenthat is causing a lot of social, laborand environmental harms and that is
ultimately why I evoke this analogy toempire.>> And Karen, could you talk some moreabout not only the energy requirements
but the water requirements of these hugedata centers that are essence in essencethe backbone of of this uh widening uh
industry?
>> Absolutely. I'll give you two stats onboth the energy and the water. Whentalking about the energy demand,
McKenzie recently came out with a reporthat said in the next 5 years based onthe current pace of AI computational
infrastructure expansion, we would needto put as much energy on the global gridas what is consumed by two to six times
the energy consumed annually by thestate of California. And that willmostly be serviced by fossil fuels.We're already seeing reporting of uh
coal plants with their lives beingextended. They were supposed to retirebut now they cannot to support this data
center development. We are seeingmethane gas turbines, unlicensed onesbeing popped up to uh service these data
centers as well. From a freshwaterperspective, these data centers need tobe trained on freshwater. They cannot be
trained on any other type of waterbecause it can corrode the equipment. Itcan lead to bacterial growth and most of
the time it actually taps directly intoa public drinking water supply becausethat is the infrastructure that has been
laid to deliver this clean fresh waterto different businesses to differenthomes. And Bloomberg recently had an
alysis where they looked at thexpansion of these data centers aroundthe world and 2thirds of them are being
placed in water scarce areas. So they'rebeing placed in communities that do nothave access to fresh water. So it's not
just the total amount of fresh waterthat we need to be concerned about, butactually the distribution of this
infrastructure around the world.And most people are familiar with chatGPT the consumer aspect of AI but what
about the military uh aspect of AI wherein essence uh we're finding SiliconValley companies becoming the next
generation of defense contractors.>> One of the reasons why OpenAI and manyother companies are turning to the
defense industry is because they havespent an extraordinary amount of moneyin developing these technologies.
They're spending hundreds of billions totrain these models and they need torecoup those costs and there are only so
many industries and so many places thathave that size of a paycheck to pay. Andso that's why we're seeing a cozying up
to the defense industry. We're alsoseeing Silicon Valley use the USgovernment in their empire buildingambitions. You could argue that the US
government is also trying to use SiliconValley vice versa in their empirebuilding ambitions. Um but certainly
these technologies are not they are notdesigned to be used in a sensitivemilitary context. And so the theaggressive push of these companies to
try and get those defense contracts andintegrate their technologies more andmore to the into the infrastructure of
the military is really alarming. Iwanted to go to the countries you wento or the stories you covered because I
mean this is amazing the depth of youreporting from Kenya to Uruguay toChile. Um you were talking about the use
of water and I also want to ask youabout nuclear power. Uh but in Chile umwhat is happening there around these
data centers and the water they woulduse and the resistance to that.>> Yeah. So Chile has an interestinghistory in that it's been under it was
under a dictatorship for a very longtime. And so during that time, mostpublic resources were privatized,including water. But because of an
omaly, there's one community in thegreater Santiago metropolitan regionthat actually still has access to a
public freshwater resource that servicesboth that community as well as the restof the country in emergency situations.
That is the exact community that Googlechose 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 thecommunity told me was they weren't evenpaying taxes for this because they they
believed based on reading thedocumentation that the taxes that Googlewas paying was in fact to where they had
registered their offices, theiradministrative offices, not where theywere putting down the data center. So
they were not seeing any benefit fromthis data center directly to thatcommunity and they were seeing no checks
placed on the fresh water that this datacenter would have been allowed toextract. And so these activists said,
"Wait a minute, absolutely not. We'renot going to allow this data center tocome in unless they give us a legitimate
reason for why it benefits us." And sothey started doing boots on the groundactivism, pushing back, knocking on
every single one of their neighborsdoors, handing out flyers to thecommunity, telling them this company is
taking our freshwater resources withoutgiving us anything in return. And sothey escalated so dramatically that it
escalated to Google Chile. It escalatedto Google Mountain View, which by theway then sent representatives to Chile
that only spoke English.But then it eventually escalated to theChilean government. And the Chileangovernment now has roundts where they
ask these community residents and thecompany representatives andrepresentatives from the government to
come together to actually discuss how tomake data center development morebeneficial to the community. The
activists say it is the fight is notover. Just because they've been invitedto the table doesn't mean thateverything is suddenly better. They need
to stay vigilant. They need to continuescrutinizing these projects. But thusfar they've been able to block this
project for four to five years and havegained that seat at the table.>> And how is it that these uh westerncompanies 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 AIsystems are trained on massive amountsof data and they're sc that's scraped
from the internet, you can't actuallypump that data directly into your AImodel because there are a lot of things
within within that data. It's heavilypolluted. It needs to be cleaned. Itneeds to be annotated. So this is where
data annotation firms come in. These aremiddleman firms that hire contract laborto provide to these AI companies to do
that kind of data preparation. And openAI when it was starting to think aboutcommercializing its products and
thinking about let's put text generationmachines that can spew any kind of textinto the hands of millions of users.
They realized they needed to have somekind of content moderation. They neededto develop a filter that would wrap
around these models and prevent thesemodels from actually spewing racist,hateful, and harmful speech to users
that would not make a very goodcommercially viable product. And so theycontracted these middleman firms in
Kenya where the Kenyan workers had toread through reams of the worst text onthe internet as well as AI generated
text where open AI was prompting its ownAI models to imagine the worst text onthe internet and then telling these
Kenyan workers to detail to categorizethem in detailed taxonomies of is thisexual content, is this violent content,
how graphic is that violent content inorder to teach its filter all thedifferent categories of content it had
to block. And this is incrediblyuncommon form of labor. There are lotsof other different types of contract
labor that they use. But these workers,they're paid a few bucks an hour, if atall. And just like the era of social
media, these content moderators are leftvery deeply psychologically traumatized.And ultimately, there is no real
philosophy behind why these workers arepaid a couple bucks an hour and havetheir lives destroyed. And why AI
researchers who also contribute to thesemodels are paid million-dollcompensation packages simply because
they sit in Silicon Valley in OpenAI'soffices. That is the logic of Empire.And that hearkens back to my title,
Empire of AI.>> So, let's go back to your title, Empireof AI. the subtitle dreams andnightmares in Sam Alman's Open AI. So
tell us the story of Sam Alman and whatOpen AI is all about right through tothe deal he just made in the Gulf when
President Trump uh Sam Alman and ElonMusk were there. Alman is very much aproduct of Silicon Valley. His career
was first as a founder of a startup andthen as the president of Y Combinator,which is one of the most famous startup
accelerators in Silicon Valley, and thenthe CEO of OpenAI. And there's nocoincidence that OpenAI ended up
introducing the world to the scale atall cost approach to AI developmentbecause that is the way that Silicon
Valley has operated in the entire timethat Altman came up in it. And so he isa very strategic person. He isincredibly good at telling stories about
he future and painting these sweepingvisions that investors and employeeswant to be a part of. And so early on at
YC, he identified that AI would be oneof the trends that could take off. Andhe was trying to build a portfolio of
different investments and differentinitiatives to place himself in thecenter of various different trends
depending on which one took off. He wasinvesting in quantum computing. He wasinvesting in nuclear fusion. He was
investing in self-driving cars. And hewas developing a fundamental AI researchlab. Ultimately, the AI research lab was
the ones that started acceleratingreally quickly. So he makes himself theCEO of that company. Um and andoriginally he started it as a nonprofit
o try and position it as a counter toforprofit driven incentives in SiliconValley. But within one and a half years,
OpenAI's executives identified that ifthey wanted to be the lead in thispace, they had to go for this scale at
all cost approach and had to should bein quotes. They thought that they had todo this. There are actually many other
ways to develop AI and to have progressin AI that does not take this approach.But once they decided that, they
realized the bottleneck was capital. Itjust so happens Sam Alman is a once in ageneration fundraising talent. He
created this new structure nesting afor-profit arm within the nonprofit tobecome this fundraising vehicle for the
tens of billions and ultimately hundredsof billions that they needed to pursuethe approach that they decided on. And
that is how we ultimately get to presentday OpenAI, which is one of the mostcapitalistic companies in the history of
Silicon Valley, continuing to raisehundreds of billions and and Altman hasjoked even trillions to produce a
technology that ultimately has amiddling economic impact thus far. We'llreturn to our conversation in a minute
with Karen How, author of the new bookEmpire of AI: Dreams and Nightmares inSam Alman's Open AI. Stay with us.
This is Democracy Now! democracynow.org.
I'm Amy Goodman. In this holidayspecial, we continue with the journalistKaren How, author of the new book Empire
of AI: Dreams and Nightmares, and SamAlman's Open AI. Karen came into ourstudio in May when she discussed how AI
will impact workers.One of the things that we have seen isthis technology is already having a hugeimpact on jobs.
Not necessarily because the technologyitself is really capable of replacingjobs, but it is perceived as capable
nough that executives are laying offworkers. And we need more some kind ofmore guard rails to actually prevent
hese companies from continuing to tryand develop labor automatingtechnologies and try to shift them toproducing labor assistive technologies.
What do you mean?
>> So, open AI, their definition of whathey call artificial generalintelligence is highly autonomousystems that outperform humans in most
economically valuable work. So, theyexplicitly state that they are trying toautomate jobs away. I mean, what are
what is economically valuable work? But
he things that people do to get paid.Um but there's this really great bookcalled Power in Progress by MITeconomists Jeron Austin and Simon
Johnson who mention that technologydevelopment all technology revolutionsthey take a labor automating approach
not because of inevitability but becausethe people at the top choose to automatethose jobs away. They choose to design
the technology so that they can sell ito executives and say you can shrinkyour costs by laying off all theseworkers and using our AI services
instead. But in the past, we've seenstudies that for example suggest that ifyou develop an AI tool that a doctor
uses rather than replacing the doctor,you will actually get better health carefor patients. you will get better di
cancer diagnoses. If you develop an AItool that teachers can use rather thanjust an AI tutor that replaces the
teacher, your kids will get bettereducational outcomes. And so that's whatI mean by labor assistive than labor
>> and explain uh what you mean because Ithink a lot of people don't evenunderstand artificial intelligence. And
when you say replace the doctor, whatare you talking about?
>> Right. So these companies they try todevelop a technology that they positionas an everything machine that can do
anything. Um and so they will try to sayou can use this you can talk to chatbtfor therapy. No, you cannot. Chat GBT is
not a licensed therapist. And in fact,these models actually spew lots ofmedical misinformation. And there have
been lots of um examples of actuallyusers being psychologically harmed bythe model because the model will
continue to reinforce um selfharmingbehaviors. And we've even had caseswhere uh children who speak to chatbots
and develop huge emotional relationshipswith these chatbots have actually killedthemselves after using these chatbot
systems. Um but that's what I mean whenthese companies are trying to developlabor automating tools. They're
positioning it as you can now hire thistool instead of hire a worker. I mean,most recently, Sam Alman was speaking at
a conference and said, "We originallysaid that these models were junior levelpartners at a law firm, and now we think
that they can really be more seniorcolleagues at a law firm." What he'saying is don't hire the junior levelpartners, don't hire the senior
colleagues, and just use our AI models.And we are already seeing the careerladder breaking because many different
white collar job uh white collar serviceindustries as well as other industriesare becoming convinced that they do not
need to hire interns. They do not needto hire entry-level positions that theyjust need these AI models and new
college graduates are struggling now tofind job opportunities to help them geta foothold into these industries. So,
you've talked about Sam Alman, and inpart 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 hexploded onto the um US scene,testifying before Congress, actuallywarning 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 talkabout the other kind of prophet, P O Fit
T.um and how open AI was formed. How isopen AI different from AI?
OpenAI is a com I mean it was originallyfounded as a nonprofit as I mentionedand Alman specifically when he was
thinking about how do I make afundamental AI research lab that isgoing to make a big splash he chose tomake it a nonprofit because he
identified that if he could not competeon capital and he was relatively late tothe game Google already had a monopoly
on a lot of top AI research talent athe time if he could not compete oncapital and he could not compete um interms of being a first mover he
needed some other kind of ingredienthere to really recruit talent recruitum public goodwill and establish a name
for open AAI so he identified a missionhe identified let me make this anonprofit and let me give it a reallycompelling mission so the mission of
openai is to ensure artificial generalintelligence benefits all of humanityAnd one of the quotes that I open my
book with is this quote that Sam Almancited himself in 2013 um in his blog. Hewas an avid blogger back in the day
talking about his learnings on businessand strategy and Silicon Valley startuplife. And the quote is successful people
built companies, more successful peoplebuild countries. The most successfulpeople build religions. And then he
reflects on that quote in his blogsaying, "It appears to me that the bestway to build a religion is actually to
build a company.">> And so talk about how Alman was thenforced out of the company and then cameback. And also I just found it so
fascinating that you were able to speakwith so many Open AI workers. Youthought there was a kind of total ban on
you.>> Yes. Yeah. Exactly. So I was the firstjournalist to profile OpenAI. Um, Iembedded within the company for 3 days
in 2019 and then my profile published in2020 for MIT technology review and athe time I identified in the profile
this tension that I was seeing where itwas a nonprofit by name but behind thescenes a lot of the public values that
hey exposed were actually the oppositeof how they operated. So they espousedtransparency but they were highly
secretive. They espousedcollaboriveness. They were highlycompetitive. and they espoused that theyhad no commercial intent, but in fact it
seemed like they had just gotten a $1billion investment from Microsoft. Itseems like they were rapidly going to
develop commercial intent. And so Iwrote that into the profile and OpenAIwas deeply unhappy about it and they
would not refuse to talk to me for 3years. But when I started working on thebook, when I started reaching out to
employees, current and former, Idiscovered that many employees actuallyreally liked the profile and they
specifically wanted to talk to mebecause they thought that I would dojustice to the truth of what hadactually happened within the company and
be able to discover behind what thexecutives mythologized and narrativizedabout this technology [clears throat]
and about the course of this company. Iwould be able to actually get beneathat to the real heart of the matter.
And so um one of the things that youreally have to understand about AIdevelopment today is that there are what
I call quasi religious movements thathave developed within Silicon Valley.The concept of artificial general
intelligence is not one that'scientifically grounded. It is this ideathat we can fundamentally recreate human
intelligence in computers. And this ideahas been around for actually a reallylong time. The field of AI was founded
all the way back in the 1950s and thatwas the original intent of the field.How do we recreate intelligence in
computers? Can machines think? That was
the famous question that Britishmathematician Alan Turing asked. But weto this day do not have scientific
onsensus around even what humanintelligence is. And so to peg an entiresearch field and a technology to the
basis of human intelligence is a verytricky endeavor because there are nogood metrics to assess have we actually
gotten there yet and there's noblueprint to say what should AI looklike and how should it work andultimately who should it serve. And so
when OpenAI took up this mission ofartificial general intelligence, theywere able to essentially shape and mold
what they wanted this technology to bebased on what is most convenient forthem. But when they identified it, it
was at a time when scientists reallylooked down on this term even AGI. Andso they absorbed just a small group of
self-identified AGI believers. This iswhy I call it quasi religious becausethere's no scientific evidence that we
can actually develop AGI. The people whoare strongly con have this strongconviction that they will do it and that
it's going to happen soon. It is justpurely based on belief and they talkabout it as a belief too. But there are
two factions within this belief systemof the AGI religion. There are peoplewho think AGI is going to bring us to
utopia and there are people who thinkAGI is going to destroy all of humanity.Both of them believe that it ispossible. It's coming soon. And
therefore they conclude that they needto be the ones to control the technologyand not democratize it. And this is
ultimately what leads to your questionof what happened when Sam Alman wasfired and rehired through the history of
OpenAI. There's been a lot of clashingbetween the boomers and doomers aboutwho should actually>> the boomers and doomers.
>> The boomers and the doomers. [laughter]>> Those that say it'll bring us theapocalypse. topia boomers and those that
say it'll destroy humanity. The doomersand they have clashed relentlessly andaggressively about how quickly to build
the technology, how quickly to releasethe technology and ultimately Altman isone that he is really good at saying to
people what they need to hear and hewill say different things to differentpeople if he thinks they need to hear
different things. So when I askedboomers, is Altman a boomer? They said
yes. When I asked doomers, is Altman adoomer? They said yes. And I want to
take this up until today to um inJanuary, the Trump administrationannouncing the Stargate project, a $500
billion project to boost AIinfrastructure in the United States.This is Open AI Sam Alman speakingalongside President Trump.
I think this will be the most importantproject of this era and as Masa said forAGI to get built here to create hundreds
of thousands of jobs to create a newindustry centered here. Uh we wouldn'tbe able to do this without you Mr.President.
>> He also there referred to AGI um uhartificial general intelligence. Explainwhat happened here and what this is and
has it actually happened. So Altmanbefore Trump was electedum he already was sensing throughobservation that it was possible that
he administration would shift and thathe would need to start politicking quiteheavily to ingruiate himself to a new
administration.Alman is very strategic. Um he was undera lot of pressure at the time as wellbecause his original co-founder Elon
Musk now has great beef with him. UhMusk feels like Alman used his name andhis money to set up OpenAI and then he
got nothing in return. So Musk had beensuing him, still suing him and suddenlybecame first buddy of the Trump
administration. So Altman basicallycleverly orchestrateda um this announcement where by the waythe the announcement is quite strange
because the Trump President Trump is notit's not the US government giving $500billion. It's private investment coming
into the US um from places like SoftBank>> which is>> uh which is one of the largestinvestment funds um run by Masay Yoshi
Son a Japanese businessman who made alot of his wealth from the previous techera. So, so it's not even the USgovernment that's that's providing this
money.>> And take that right through to now thatGulf trip that um Elon Musk was on, butso was Sam Alman to the fury of Elon
Musk and then a deal was sealed in AbuDhabi.>> Yeah.>> It didn't include Elon Musk but wasabout open AI.>> Exactly. So Altman has continued to try
and use the US government as a way to toget access to more places and uh morepowerful spaces to build out thisempire. And one of the one of the things
because OpenAI's computationalinfrastructure 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 inthe US which is why they're trying to
get access to land and energy in otherplaces. The Middle East has a lot ofland and has a lot of energy and they're
willing to strike deals and that is whyAltman was part of that trip looking tostrike a deal and what they the deal
that they struck was to build a massivedata center or multiple data centers inthe Middle East using their land and
their energy. But one of the things thatOpenAI has recently rolled out, theycall it the OpenAI for countries program
and it is this idea that they want toinstall OpenAI hardware and software inplaces around the world and explicitly
says we want to build democratic AIrails.We want to install our hardware andsoftware as a foundation of democratic
AI globally so that we can stop Chinafrom installing authoritarian AIglobally. But the thing that he does not
acknowledge is that there is nothingdemocratic about what he's doing. Youknow, the Atlantic executive editor says
we need to call these companies for whathey are. They are technoauthoritarians. They do not ask thepublic for any perspective on how they
develop the technology, what data theytrain the technology on, where theydevelop these data centers. In fact,
these data centers are often developedin the cover of night um under shellcompanies like Meta recently entered New
Mexico under the Shell company namedGreater Kudu LLC.>> Greater Kudu.LLC. And once the deal wasactually 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 yourfresh water.>> And then there was this wholecontroversy in Memphis around a data
center.>> Yes. So that is the data center thatElon Musk is building. So meanwhile,Musk is saying Alman is terrible.
Everyone should use my AI. And ofcourse, his AI is also being developedusing the same environmental and public
health costs. So he built this massivesupercomputer called Colossus inMemphis, Tennessee that's training
Grock, the chatbot that people canaccess through X and that is beingpowered byaround 35 unlicensed methane gas
turbines that are pumping thousands oftons of toxic air pollutants into thegreater Memphis community. And that
community has long suffered a lack ofaccess to clean air, a fundamental humanright.>> So I want to go to interestingly Sam
Alman testifying in front of Congressabout solutions to the high energyconsumption of artificial intelligence.
>> In the short term, I think this probablylooks like more natural gas. Um althoughthere are some applications where I
think solar can really help. In themedium-term, I hope it's advancednuclear uh fish and fusion. More energy
is important well beyond AI.>> So that's open AI's Sam Alman. This istestifying before the Senate and talking
about everything from uh solar tonuclear power. Something that was foughtin the United States by environmental
activists for decades. So you have thesehuge old uh nuclear power plants, butmany say you can't make them safe no
matter how small. and smart you makethem.>> This is one of the things of the manythings that I'm concerned about with the
current trajectory of AI development.This is a second order tertiary ordereffect is that because these companies
are trying to claim that the AIdevelopment approach they took doesn'thave climate harms. They are explicitly
evoking nuclear again and again andagain as nuclear will solve the problem.And it has been effective. I have talked
with certain AI researchers who thoughthe problem was solved because ofnuclear and in order to try and actually
build more and more nuclear plants, theyare lobbying governments to try andunwind the regulatory structure around
nuclear power plant building. I meanthis is this is like crazy on so manylevels that they're not just trying to
develop these the AI technologyrecklessly. They are also trying to laydown infrastructure and nuclearinfrastructure in this move fast break
things ideology. But for those who umare environmentalists and have longopposed nuclear will they be sucked in
by the solar alternative? But that exact
so data centers have to run 247. So theycannot actually run on just renewables.That is why the companies keep trying to
evoke nuclear as the solve all but solardoes not actually work when we do nothave sufficient enough energy storage
solutions for that 24/7 operation. We'llreturn to our conversation in a minutewith Karen How, author of the new book
Empire of AI: Dreams and Nightmares inSam Alman's Open AI. Stay with us.This is Democracy Now! Democracynow.org.
I'm Amy Goodman. In this holidayspecial, we're speaking with thejournalist Karen How, author of the newbook Empire of AI: Dreams and Nightmares
in Sam Alman's Open AI. She came intour studio in May. She lives in HongKong. I asked her to talk about what'shappening in China around artificial
intelligence.>> China and the US are the largest hubsfor AI research. They are the largestconcentration of AI research talent
globally. Um, China other than SiliconValley, China really is the only otherival in terms of talent density and the
amount of capital investment and theamount of infrastructure that is goinginto AI development. In the last few
years, what we have seen is the USgovernment has been aggressively tryingto stay number one and one of themechanisms that they have used is export
controls. A key input into these AImodels is the computationalinfrastructure and the computer chipsfor installing into the data centers for
training these models. And thesecomputer chips are the in order todevelop the AI models. Companies areusing the most bleeding edge computer
chip technology. It's like the every twoyears a new chip comes out and theyimmediately start using that to train
the next generation of AI models. Thosecomputer chips are designed by Americancompanies, the most prominent one being
Nvidia in California. And so the USgovernment has been trying to use exportcontrols to prevent Chinese companies
from getting access to the most cuttingedge computer chips. That has all beenunder the recommendation of Silicon
Valley saying this is the way to preventChina from being number one. and likeput export controls on them and don't
regulate us at all so we can stay numberone and they will fall behind. What hashappened insteadis because there is a strong base of
talent of AI research talent in Chinaunder the constraints of fewercomputational resources, Chinesecompanies have actually been able to
innovate and develop the same level ofAI model capabilities as Americancompanies with two orders of magnitude
less computational resources, lessenergy, less data. So, I'm talkingspecifically about um the Chinesecompany Highfire, which developed this
model called Deep Seek earlier this yearthat briefly tanked the global economybecause the company said that their
um training this one AI model costaround $6 million when OpenAI wastraining models that cost hundreds ofmillions if not over tens of billions of
dollars. And that delta demonstrated topeople that this what Silicon Valley hastried to convince everyone for the last
few years that this is the only path togetting more AI capabilities is totallyfalse and actually the techniques that
chi the Chinese company was using wereones that existed in the literature andjust had to be assembled. They used a
lot of engineering sophistication to dothat, but they weren't actually usingfundamentally new techniques. They were
ones that actually already existed.>> So explain it further because I think alot of people just can't get their minds
around this. How do you do thistraining?
>> So there's software called neuralnetworks which is essentially a massivestatistical engine. is doing lots and
lots of sophisticated statisticalcomputation to try and ascertain whatkinds of patterns exist in data sets. So
typically in in the past before we goto large language models it would bedoing something like um looking at MRI
scans and checking the patterns of whatdoes cancer look like in an MRIscan. Um now with GBT what it's looking
at is what are the patterns of theEnglish language? what is the syntax,
the structure, figures of speech thatare typically used and then it usesthose patterns to construct newsentences. That's how generative AI
works. And the reason why it's socomputationally expensive is becauseit's crunching the numbers for those
patterns. And the more data you feed in,the more it has to crunch. And so it weused to train these AI models on you
know a powerful laptop like maybe onecomputer chip maybe the richest labsacademic labs like MIT they would be uh
training on a couple or a dozen computerchips and companies like Google theywould be training maybe on a couple
hundred computer chips. We are nowtalking about hundreds of thousands ofcomputer chips training a single model.
Um and that is the you know that is whatopen AI says is necessary to build thesetechnologies and that is what deepseek
proved wrong. So, let me ask yousomething, Karen. uh the latest news umas you're traveling in the United States
before you go back to Hong Kong uh ofTrump's attack on academia, how thisfits in. Um how could Trump's attack on
international students specificallytargeting the what more than 250,000 aquarter of a million Chinese students
and revoking their visas impact thefuture of the AI industry. But not justChinese students because what's going on
here now is terrifying students aroundthe world and because labs are shuttingdown in all kinds of ways here uh US
students as well uh deciding to goabroad.This is just the latest action that theUS government has taken over the last
few years to really alienate a keytalent pool for US innovation.Originally, there were more Chineseresearchers working in the US
contributing to US AI than there were inChina because [snorts] just a few yearsago, Chinese researchers aspired to work
for American companies. They wanted tomove to the US. They wanted tocontribute to the US economy. Theydidn't want to go back to their home
country. But because of what was calledthe China Initiative, which was the afirst Trump era initiative to try and
criminalize Chinese academics orethnically Chinese academics, some ofwhom were actually Americans um based on
just paperwork errors. They would accusethem of being spies. That was one of thefirst actions. Then of course the
pandemic happened and the USChina tradescalations started amplifyinganti-Chinese rhetoric. All of these led
and now with the potential ban oninternational students. All of thesehave led more and more Chineseresearchers to just opt for staying at
home and contributing to the Chinese AIecosystem. And this was a prerequisiteto High-fly pulling off Deepseek. If
there had not been that concentrationand buildup of AI talent in China, theyprobably would have had a much harder
time innovating around circumventingthese export controls that the USgovernment was imposing on them. But
because they now have a highconcentration of top talent, some of thetop talent globally,when those restrictions were imposed,
they were able to innovate around them.So Deepseek is literally a product ofthis continuation of that alienation and
with the US continuing to take thistance, it is just going to get worse.And as you mentioned, it's not justChinese researchers. I literally just
alked to a friend in academia that saidshe's considering going to Europe nowbecause she just cannot survive without
hat public funding. And Europe Europeancountries are seeing a criticalopportunity offering milliondoll
packages. Come here, we'll give you alab. We'll give you millions of dollarsof funding. I mean this is the fastest
way to brain drain this country.>> I mean what many are saying US's braindrain is their brain gain. Yes.>> And this also reminds us of history. You
have the Chinese rocket scientist ChenShuen who in the 1950s was inexplicablyheld under house arrest for years and
then Eisenhower has him deported toChina. He becomes the father of rocketscience and uh China's entry into space.
And he said he would never again stepfoot into the United States even thoughoriginally that was the only place he
wanted to live.>> Yes. And there was a I believe agovernment official, a US governmentofficial who said that was the dumbest
mistake the US ever made.>> Um you we talk about the brain drain andthe brain gain. Okay. Again, uh somemore rhyming, the doomers and the
boomers. Um, I want to talk about whatan AI apocalypse looks like, meaning howit brings us to apocalypse, but also um
how uh people say it could lead us to autopia. What are the two trackstrajectories?
>> It's a great question and I ask boomersand doomers this all the time. Can youarticulate to me exactly how we get
here? And the issue is that they
cannot. And this is why I call it quasireligious. It really is based on belief.I mean, I was talking with oneresearcher who identified as a boomer.
And I said, you know, he his his eyeswere wide and he he really lit upsaying, you know, once we get to AGI,game over. Everything becomes perfect.
And I asked him, I was like, can youexplain to me how does AGI feed peoplethat haven't don't have food on thetable right now? And he was like, "Oh,
you're talking about like the floorand how to elevate their qualityof life." And I was like, "Yes, becausethey are also part of all of humanity."
And he was like, "I'm not really surehow that would happen, but I think itcould it could help the middle class get
more economic opportunity." And I waslike, "Okay, but how does that happen aswell?" And he was like, "Well, once
these come once we have AGI and it canjust create trillions of dollars ofeconomic value, we can just give them
cash payouts." And I was like, who'sgiving them cash payouts? What
institutions are giving them? You know,
like it it doesn't when you actuallytest their logic, it doesn't reallyhold. And with the doomers, I mean, it's
the same thing. like their belief isultimatelywhat I realized when reporting on thebook is they believe AGI is possible
because of their belief of how the humanbrain works. They believe humanintelligence is inherently fullycomputational. So if you have enough
data and you have enough computationalresources, you will inevitably be ableto recreate human intelligence. It's
just a matter of time. And to them, thereason why there would that would leadto an apocalyptic scenario is humans, we
learn and improve our intelligencethrough communication. And communicationis inefficient. We miscommunicate all
the time. And so for AI intelligences,they would be able to rapidly getsmarter and smarter and smarter byhaving perfect communication with one
another as digital intelligences. And somany of these people who selfidentify asdoomers say there has never been in the
history of the the universe a speciesthat was superior to another species a aspecies that was able to rule over um a
more superior species. So they thinkthat ultimately AI will evolve into ahigher species and then start ruling us
and then maybe decide to get rid of usaltogether. I'm wondering if you cantalk about any model of a country, not a
company,>> that is pioneering a way ofdemocratically controlled artificialintelligence.>> I don't think it's actively happening
right now.The EU has had the EU AI act, which istheir major piece of legislation tryingto develop a riskbased, rightsbased
framework for governing AI umdeployment.Buto me, one of the keys of democratic AIgovernance is also democratically
developing AI. And I don't think anycountry is really doing that. And what Imean by that is there are AI has asupply chain. It needs data. It needs
land. It needs energy. It needs water.And it also needs spaces in which thesecompanies need access to to then deploy
their technology. Schools, hospitals,government agencies. Silicon Valley hasdone a really good job over the last
decade of making people feel that theircollectively owned resources are SiliconValleys. You know, I have I talk with
friends all the time who say, "We don'thave 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 thatdata is yours. You know, thatintellectual property is the writers andartists intellectual property. That land
is a community's land. Those schools arethe students and teachers schools. Thehospitals are the doctors and nurses and
patients hospitals. These are all sitesof democratic contestation in thedeployment in the development and the
deployment of AI. And just like thoseChilean water activists that we talkedabout who aggressively understood that
fresh water was theirs and theywere not willing to give it up unlessthey got some kind of mutuallybeneficial agreement for it. We need to
have that spirit in protectingour data, our land, our water, and ourschools so that companies inevitablywill have to adjust their approach
because they will no longer get accessto the resources they need or the spacesthat they need to deploy in. In 2022,
Karen, you wrote a piece for MITechnology Review headlined a new visionof artificial intelligence for the
people. In a remote rural town in NewZealand, an indigenous couple ischallenging what AI could be and who it
should serve. Who are they? This was a
wonderful story that I did where thecouple um they run to media. It's anonprofit MAI radio station in NewZealand. And the Maui people have
suffered a lot of the same um challengesas many indigenous peoples around theworld. The history of colonization led
them to rapidly lose their language andthere are very few Mauy speakers in theworld anymore. And so in the last few
years there's been an attempt to revivethe language and the New Zealandgovernment has tried to repent by by
trying to encourage that the revival ofthat language. But this nonprofit radiostation, they had all this wonderful
archival material, archival audio oftheir ancestors speaking the Mailanguage that they wanted to provide to
Maui speakers, ma Mai learners aroundthe world as an educational resource.The problem is in order to do that they
needed to transcribe the audio so thatMai learners could actually listen, seewhat was being said, click on the words,
understand the translation and actuallyturn it into an active learning tool.But there were so few Maui speakers that
can speak at that advanced level thathey realized they had to turn to AI.And this is a key part of my book'sargument is I'm not critiquing all AI
development. I'm specifically critiquingthe scale at all cost approach thatSilicon Valley has taken. But there are
many different kinds of beneficial AImodels, including what they ended updoing. So they took a fundamentally
different approach. First and foremost,they asked their community, do we wanthis AI tool? Once the community said
yes, then they moved to the next step ofasking people to fully consent todonating data for the training of this
tool. They explained to the communitywhat this data was for, how it would beused, how they would then guard that
data and make sure that it wasn't usedfor other purposes.They collected around a couple hundredhours of audio data in just a few days
because the community rallied supportaround this project and only a couplehundred hours was enough to create a
performant speech recognition modelwhich is crazy when you think about thescales of data that these Silicon Valley
companies require. And that is onceagain a lesson that can be learned isactually there's plenty of research that
shows when you have highly curated smalldata sets, you can actually create verypowerful AI models and then once they
had that tool, they were able to doexactly what they wanted to open sourceand resour uh open source thiseducational resource to their community.
And so my vision for AI development inthe future is to have more smalltaskspecific AI models that are notrained on vast polluted data sets but
small curated data sets and thereforeonly need small amounts of computationalpower and can be deployed in challenges
that we actually need to tackle forhumanity.mitigating climate change by integratingmore renewable energy into the grid,
improving health care, by doing moredrug discovery.>> So, as we finally do wrap up, what youwere most shocked by, you've been doing
uh this journalism, this research foryears, what you were most shocked by inwriting Empire of AI.I originally thought that I was going to
write a book focused on vertical harmsof the AI supply chain. Here's how laborexploitation happens in the AI industry.
Here's how the environmental harms arearising out of the AI industry. And athe end of my reporting, I realized that
here is a horizontal harm that'shappening here. Every single communitythat I spoke to, whether it was artists
having their intellectual property takenor Chilean water water activists havingtheir fresh water taken, they all said
that when they encountered the empire,they initially felt exactly the sameway. A complete loss of agency to
self-determine their future. And that iswhen I realized the horizontal harm hereis AI is threatening democracy. If the
majority of the world is going to feelthis loss of agency overself-determining their future, democracycannot survive and again specifically
Silicon Valley's approach scale at allcosts AI development.>> But you also chronicle the resistance.You talk about how the Chilean water
actors felt at first, how the artistsfeel at first. So talk about thestrategies that these people havemployed and if they've been effective.
>> So the amazing thing is that there hasince been so much push back. Theartists have then said wait a minute we
can sue these companies. The Chileanwater activists said wait a minute wecan fight back and protect these water
esources. The Kenyan workers that Ispoke to who are contracted by OpenAIthey said we can unionize and escalate
our story to international mediattention. And so even in these evenwhen I thought that these communitiesyou could argue are the most vulnerable
in the world have the least amount ofagency, they were the ones thatremembered that they do have agency andthat they can seize that agency and
fight back. And I think it it was it wasremarkably heartening to encounter thosepeople to remind me that actually the
first step to reclaiming democracy isremembering that no one can take youragency away.>> Karen How, author of the new book Empire
of AI: Dreams and Nightmares and SamAlman's Open AI. Karen How is a formereporter at the Wall Street Journal and
MIT Technology Review. And that does itfor this special broadcast. [music]Democracy Now is produced with Mike
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