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0:00 Democracy depends on a free press. Please support our independent journalism at democracynow.org/g. This is democracyow democracynow.org. The Warren Peace Report. I'm Amy Goodman with Juan Gonzalez. We turn now to the Empire of AI. That's the name of a new book by the journalist Karen How, who's closely reported on the rise of the artificial intelligence industry with a focus on Sam Alman's Open AI, the company behind Chat GPT. Karen How compares the actions of the AI industry to those of colonial powers in 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
0:46 seize and extract precious resources to feed their vision of artificial intelligence, the work of artisan 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, "Karen House book comes at a time when Republican Congress members are trying to block states from regulating AI. The House recently passed Trump's so-called big beautiful budget bill that contains a provision that would prohibit any state level regulations of AI for the next decade." In a major gift to the AI industry, Republican Congresswoman Marjorie Taylor Green has criticized the provision even though she voted for the
1:32 bill. She wrote online, quote, "Full transparency. I did not know about this section. I'm adamantly opposed to this and it's a violation of state rights and I would have voted no if I had known this was in there." She says she won't vote for it if it remains in there after the Senate votes. To talk about this and much more, we're joined by the journalist Karen How, whose new book again is just out, Empire of AI: Dreams and Nightmares, and Sam Alman's Open AI. former reporter at the Wall Street Journal and MIT Technology Review. She leads the Pulitzer Cent's AI Spotlight Series program for J training journalists on how to cover AI. You should train everyone on how to understand AI. Karen, it's an amazing book. Why don't you start by talking
2:18 about the title, what exactly you mean for a lay audience for I suspect a lot of our audience are lites. Um, so you really have to explain what artificial intelligence, artificial general 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.
3:05 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
3:51 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 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
4:37 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
5:23 where they looked at the expansion of these data centers around the world and twothirds 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 uh 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
6:08 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
6:55 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,
7:42 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 they proposed for their data center to use a thousand times more fresh water than that community used annually. 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,
8:28 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
9:14 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
10:01 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
10:47 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 OpenAI 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
11:33 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
12:18 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
13:05 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
13:50 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, opening eyes 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
14:36 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. And uh we only have about a minute left, but
15:22 the relationship between Altman and other rivals like like Google or Elon Musk. It is accelerating the development of this technology that again I I mentioned has this middling impact. We've seen through the history of OpenAI that all of the former executives that have left have created their own rivals. So Elon Musk was one of the original co-founders, created XAI. Ilia Sudskyver was the chief scientist, created safe super intelligence. Mirror Morati was the former chief technology officer, created thinking machines lab. All of them are now competing to try and dominate this technology and try and make it in their own image. And finally, this um regulation within the so-called big beautiful bill that says AI can't be
16:09 regulated by states for a decade. This is absolutely going to enshrine the impunity of Silicon Valley into law. I mean, I call this these empires of AI because they are already quickly becoming the apex predator in the ecosystem able to act in their self-interest and that bill if passed would certainly codify that. Well, we're going to do a part two posted online at democracynow.org. Karen How is author of Empire of AI, Dreams and Nightmares, and Sam Alman's Open AI. Tune in tomorrow on Democracy Now when we speak with the British journalist Carol Cadwalader about how to survive the broligarchy. We've got three job openings, senior headline news producer, a director of audience, and a director of technology. All full-time here in New York. You can
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