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- [00:00]
Adam Lowenstein
This is an iHeart podcast. Guaranteed Human.
- [00:04]
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- [01:12]
Adam Lowenstein
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Amy Westervelt
See paypal.com risk management for details.
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- [01:59]
Amy Westervelt
Pushkin. Hello and welcome back to drilled. I'm Amy Westervelt. Today we're bringing you another installment of our ongoing series, Drilling Deep, where we speak to authors of recent books that are either about climate or about things that intersect with climate in a big way. Today is a super timely one. We're going to talk about AI. Specifically, we're going to talk about Karen Howe's new book, Empire of Dreams and Nightmares, in Sam Altman's OpenAI. In this episode, Adam Lowenstein interviews journalist Howe, who argues that AI and the profit driven infrastructure that surrounds it is a colonial project. What OpenAI boss Altman and his fellow ideologues in Silicon Valley are pursuing, Howe says, is not just corporate power, but imperial power. It makes sense when you think about the fact that AI, at its core, its most basic and ongoing purpose, is about 24 hour surveillance to keep all US plebes in line. These guys are building empires. And as history shows, empires are built on resource extraction, particularly the old fashioned kind labor, energy, minerals, land and water. It seems like almost overnight Big Tech's feel good climate promises have evaporated. They've been swapped seamlessly for slippery promises that so called artificial artificial general intelligence will solve climate. Never mind that it's a fantastic concept that has no agreed upon definition or more fundamentally that it appears nowhere close to actually existing in Big Tech's frenzied pursuit. The quote unquote hyperscale AI dominance that evangelists claim will unlock AGI as well as its expanding alliances with fossil fuel backed petro states, fossil fuel companies and authoritarian political movements. It's become an increasingly central contributor to the climate crisis. In an October conversation with Drilled, Howe discussed how Silicon Valley giants appear to be following the oil and gas industry's playbook of disinformation and deceit, how Altman and OpenAI's secrecy and disingenuous rhetoric transformed the field of AI research into into corporate PR and why the destructive trajectory of AI scale and commercialization is not inevitable, no matter what its power hungry proponents would have you believe. That conversation is coming up after this quick break. You can find a condensed written version of this interview on our website at Drill Media.
- [05:07]
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- [07:31]
Kal Penn
hey everyone, it's Kal Penn. I'm the host of Irsay The Audible and iHeart Audiobook Club. This week on the podcast, I am sitting down with Ray Porter, the narrator of Andy Weir's audiobook project, Hail Mary Massive sci fi adventure about survival and science and what happens when you wake up alone, very far from Earth.
- [07:54]
Ray Porter
I really had to make a decision because I caught myself getting that frog in my throat and starting to get teary as I'm narrating some of these sections. And it's like, okay, yo, yo, yo, is this indulgent? And I really thought about it. I was like, no. At this point it would kind of be betraying the trust the author and the listener have in telling this story if I don't go through it. But there's places in this book that deeply, emotionally affected me and I left it on the mic. That's great because it served the story. People will say like, oh my God, I cried at the end. It's like, yeah, dude, me too.
- [08:26]
Kal Penn
Listen to Irsay the Audible and iHeart audiobook club on the iHeartradio app or wherever you get your podcasts.
- [08:41]
Interviewer (Adam Lowenstein)
How does it feel having the book out? Because it's, it's a monumental achievement. I know you've gotten lots of praise for it already, but it's just, it's just epic and I can't imagine the amount of work that went into producing it.
- [08:55]
Adam Lowenstein
Yeah, it was the most intense and painful thing that I've ever worked on in my life. Like emotionally and physically painful because I was typing so much that I developed tendonitis on my hands. But yeah, no, it's. I mean, it's. I think it's been interesting. Have you ever written a book before?
- [09:18]
Interviewer (Adam Lowenstein)
It was not as long as Empire of AI, but I have some understanding of the long term nature of a writing project like this. But not to the same extent with the amount of reporting in the information that you were wrestling with here.
- [09:32]
Adam Lowenstein
The thing that I didn't really prepare for was the 180 flip from being completely alone and isolated working on the book to suddenly talking with thousands of people about the same thing once the book was launched. And that has been both a very fun and new experience and one that comes with a lot of relief that people are resonating with the thing. And also a very slightly, not slightly, an extremely chaotic transition because you go from mode of total silence and not having really feedback from anyone about anything that you're doing to suddenly getting bombarded with everyone's thoughts about what you've been working on. It's like a strange mix of relief and new sources of stress.
- [10:29]
Interviewer (Adam Lowenstein)
Since the book was released, have you heard from either sources or industry players with feedback about the book?
- [10:38]
Adam Lowenstein
I've heard from a few sources who really loved the book, which is always a relief.
- [10:44]
Interviewer (Adam Lowenstein)
Yeah. You want to do them justice for sharing their stories.
- [10:47]
Adam Lowenstein
Yeah. And I've heard from some people within industry that are not execs, but employees at these various companies that I've mentioned that were not sources, but that have mentioned that they really appreciated the book. But in terms of formal responses from OpenAI or other companies, there's been nothing, which I much prefer to a lawsuit. So I'll take silence any day.
- [11:16]
Interviewer (Adam Lowenstein)
Yeah, for sure. One of the things I found most troubling eye opening the way that you convey how artificial intelligence, or the concept of it, is an ideology in Silicon Valley and in these companies. And one of the things that the book does such a brilliant job communicating and that I wanted to convey in this conversation is the fact that these are not like normal companies and this is not a normal technology, whatever normal means. Can you talk a bit about how AI is an ideology and then how these companies are already or are pursuing this status as what you describe as empires.
- [12:03]
Adam Lowenstein
Yeah. So if you think about just the fact that if we look at the history of AI and the founding of the discipline, the scientific discipline in 1956, even back then it was already an ideological project because it was a group of scientists deciding that they wanted to try and replicate human intelligence in computers and that's a very political choice, like why do that? You know, it's not really clear what the scientific reason is. It is more of a. Of just like a. There was an intention behind that, choosing that path and setting up a field that defined its goal as attempting to mimic and therefore ultimately potentially replace humans. And Joseph Weizenbaum, an MIT professor who was kind of part of the initial cohort of scientists who did start researching AI, then later quickly became a critic of the entire endeavor still back in the 1960s. And he said at the time, in a very prophetic way, there is something inherently disturbing about a goal that intends to replace a thing that we already have. Because ultimately all this is going to do is allow people in power, politicians and corporate CEOs, to impose their will through algorithms and use the AI system as the load bearer of responsibility. Essentially it allows them to do whatever they want, but to say that something else did it. And. And so he was already recognizing back then that there's an ideological project behind the creation of AI. And so fast forward all the way to today, that ideology has not only continued to permeate and drive the industry and its goals, it has now become much more extreme because they're layered on top of this fundamental assumption that it is somehow inherently good to recreate human intelligence and computers. We now have a particular approach to doing that that these companies have indexed on, which is scaling at these models at all costs, which is also an ideology. There is no scientific basis for choosing that approach, and there's no scientific reason for why these companies are trying to dominate as monopolies. This is also based on these worldviews and values that a certain small group of people have chosen. And that group of people have an extraordinary amount of power to make that choice affect everyone. I'm really glad that you're asking about the ideological aspect of it, because I think this is a really huge part of the story of AI that is often missed. People keep thinking that this is just a business story. It's Silicon Valley doing commercial things and ultimately trying to drive for profit maximization. But that is only half the story when it comes to AI. The there is a deep ideological drive to recreate human intelligence and a belief in the idea that this is somehow going to create to solve all of our problems or potentially destroy us. And that in order to do all these things that we have to consume the entire planet's resources. And all of those need to be scrutinized for what they are, which is actually just an extremely narrow view about how the world is and how it should be.
- [15:48]
Interviewer (Adam Lowenstein)
The idea of artificial General intelligence, or AGI, I think is something people hear about a lot these days because obviously it's great for headlines and it's also great for CEOs of these companies to throw out as an idea implying that it's already here or it's just around the corner is a great way to boost a stock price. But they also, as you show in the book, they also use the idea of AGI as basically a pretext for whatever they want to do. Can you talk a little bit about what AGI is, or as close as we can come to a definition, and then how they use this hypothetical concept to basically justify whatever it is they want to do?
- [16:34]
Adam Lowenstein
Yeah. So the loosest definition of AGI is the point at which an AI system fully encapsulates all the dimensions of human intelligence, which was the original definition of AI. And the reason why we now use the term AGI instead of AI is because over the decades, the term AI has sort of been cheapened by the fact that companies keep using it to market existing products and services. And so now AI has come to mean what we have currently. And AGI is supposed to indicate a return to that original premise of this scientific discipline. But the problem why AGI is so ill defined is because we don't have scientific consensus around what human intelligence is. There's no neurological, biological, psychological definition for this special characteristic that humans seem to have more of than other animal species. And in fact, when you think about the history of trying to measure, quantify, rank human intelligence, it has always been driven by extremely dark, dark motives, eugenics, the justification of oppressing different groups of people. And so this is why AGI remains an extremely nebulous milestone, because different people have totally different ideas of what does it mean that we've finally achieved human level intelligence. And OpenAI jokes about this has been a long standing joke within the company. If you ask 13 AI researchers what AGI is, you'll get 15 definitions. And so they're kind of self aware about the fact that this lacks consensus, but it becomes a tool that the executives use to their advantage, and Altman in particular in that because there is neither a definition within the company that has full consensus, nor external to the company that has full consensus, they can just paint these visions of AGI based on whatever is necessary to overcome a particular hurdle that they're facing in that moment. So when Altman is speaking in front of Congress, he'll paint AGI as this magical system that is like A magical wand that you can wave that's going to solve climate change, cure cancer, do all these things, things that people have wanted for a very, very long time. And then when you're talking to CEOs, AGI is suddenly an employee, like something that they can buy as a service so that they don't have to hire real humans. And then when you're talking to an average consumer, AGI is suddenly a friend, or it's an assistant or whatever it is that compels that person to put down money or compels the regulators to not put in regulation. And so AGI just shape shifts and morphs in these ways that when you actually list out all of the possible things that supposedly AGI is, that Altman or any other company executive has ever said, it's a completely incoherent vision of a technology, like it just doesn't make sense. And like OpenAI uses. They've also written down in documents completely different definitions of this as well. They officially say on their website that AGI is highly autonomous systems that outperform humans in most economically valuable work. So they are defining it as a labor automating technology. But then in their contracts with Microsoft, as reported by the information, AGI is apparently an AI system that can generate $100 billion in revenue, which is like a completely different definition. So yeah, it's, it's just, it's, it's just a rhetorical tool for getting what they want.
- [20:29]
Interviewer (Adam Lowenstein)
On a side note, I'm, and I think this is probably obvious to a lot of people, but I think still bears emphasizing is the hunger that corporate CEOs have to get rid of their needy employees. And by needy I mean like healthcare benefits, vacation, parental leave, potential union organizing. They salivate at the idea of replacing workers with machines. And so you can see how the concept of AGI would be so appealing to a CEO.
- [21:00]
Adam Lowenstein
Absolutely. Yeah. And this is why this has continued in part to be a self perpetuating myth, I guess you could say that it is possible to build AGI is because there is such a high demand for that magical thing that it represents, that it is just all of the market incentives and all of the political incentives push Silicon Valley to continue propping that myth up and using it to dominate the narrative.
- [21:38]
Interviewer (Adam Lowenstein)
Something you mentioned earlier and that you trace throughout the book is the way that the promise of AGI solving the climate crisis has been used to rationalize really unfathomable environmental costs. And you describe it at one point in the book as a gamble. They're basically Saying like it doesn't really matter resource consumption, the land grabbing, not to mention the human exploitation that it requires right now. Because this magical mystery, technology will solve this crisis that we're contributing to in a massive way at some point in the future. Can you talk a bit about that gamble that they are making with the planet's chips? Even though no one actually gave them those chips to play with, but they're basically the extent to which they do not seem to care about any of the impacts of the technologies they're building because of this future promise to solve this existential crisis. It's really pretty astonishing.
- [22:41]
Adam Lowenstein
It is incredibly astonishing. Yeah. I think the first to just quantify what level of environmental impact we're talking about, there was this McKinsey report that came out earlier this year that did an estimation on how much energy would actually be required to sustain the current projections of AI industry growth. And we would need to add two to six times the amount of energy consumed by California onto the global grid in five years just to sustain the AI industry and its data center demands. That is insane. That is possibly six times the fifth largest economy in the world. And there have been other projections that have said that's more energy than all of India, the largest energy consumer at this point globally. And most of that will come from fossil fuels. So we are not only talking about an acceleration of climate change, we are also talking about an acceleration of air pollution. We are already seeing reports of methane gas turbines, for example, being used to power Colossus, the supercomputer that Elon Musk built for XAI and for training GROK in Memphis, Tennessee, that's pumping thousands of tons of pollutants into working class communities that have already had a long history of being denied the fundamental right to clean air for decades. And we also see the exacerbation of the water, the clean water crisis. There is a huge crisis of people getting access to clean drinking water around the world, in part due to the acceleration of climate change. And AI also exacerbates that. There was this investigation from Bloomberg that found that 2/3 of the data centers being built for the AI industry are going into places that are already scarce on freshwater resources. And data centers require freshwater resources to cool in order to make sure that these extremely expensive computer chips don't overheat and bust. And so you have this multi layered environmental public health crisis kind of being pushed to the brink and undermining people's fundamental ability to live a decent, quality life. And that's happening now. This is not Speculative like this is literally playing out currently. And the AI industry justifies all of this based on a speculative assumption that maybe we will get to a point where these AI systems can then fix all of those problems. And that is the thing that is so mind blowing to me is that in this AI era, somehow future speculation can be used to justify present day, real world substantial harm. And the question that I always ask people is like, how long do we wait for this potential speculative future? How much harm do we suffer before we realize that future might not arrive and we might not survive these harms? And of course, the people who are ultimately making the decisions, they're not the ones that bear the brunt of of these harms. They're not the ones that are bearing the brunt of climate having changed already, and they're not the ones breathing in this toxic air from fossil fuels burning in their communities. And so for them, the question of how long can we kind of bear to do all these things before we potentially reach euphoria is really, really long compared to most of the rest of the world.
- [26:40]
Interviewer (Adam Lowenstein)
There's a lot of ways in which the tech industry, broadly, but especially AI, if there is still any separation between the two, seems to be following the fossil fuel industry playbook. And one of those ways seems to be this narrative of A, this is inevitable, it's happening whether we like it or not, and so we might as well be the ones doing it. And B, this is the price of progress. And if you're against this, then you're against human progress. These really powerful narratives of inevitability and progress really struck me because it's the exact same rhetoric that the fossil fuel industry has been deploying in some form or another for decades.
- [27:19]
Adam Lowenstein
Yeah, that's such a great point. I mean, it is the trump card for any industry that knows that they're engaging in something that's deeply incorrect. And yeah, I mean, these technologies are not inevitable. The thing that I spent a lot of time trying to do with my book is document the moments in which OpenAI employees made decisions that fundamentally shaped the trajectory of how the technology was introduced into society based purely on whims of judgment. Technology is always a product of human choices, and sometimes those choices are actually seem really minor in the moment. Yeah. So how can it be inevitable when the shape of a technology can be swayed one way or the other based on just a person sitting in a room deciding on the fly to do one thing or another and the other thing with progress? So, yeah, this is the thing that I Hope we can have a more nuanced conversation about moving forward is there's always this idea that the tech industry perpetuates that AI is there's only one form of AI. And so if we want progress from AI, we just have to accept the costs of this progress, meaning the colossal environmental impact, the colossal public health impacts, and so on and so forth. AI is actually a collection of many different technologies that work in very different ways, that have very different cost benefit trade offs. And I often make the analogy that it's like transportation. Transportation, there's many different types of transportation. And when we talk about how we need to improve our transportation options as part of climate resiliency and fighting climate change, we're not saying like we just need more transportation, we're saying we need more bikes, we need more public transit, we need less gas guzzling trucks, we need to electrify cars. There's a much more nuanced conversation about which mode of transportation are we talking about and how to tweak and tune and adjust the supply and demand of each of these different types of transportation in order to get that progress. And we need to have a similar nuanced conversation about AI. The large scale AI models that Silicon Valley has imposed on everyone that I describe as an imperial consolidation project that is the form of AI that is the most costly and has very unclear benefits that just do not justify those costs. But when talking about the kinds of progress that we would actually want in general, putting technology aside, like things like wanting climate change to be resolved, wanting better drugs, better healthcare for treating different types of diseases, these are actually types of progress that we already know how to build AI systems for that look fundamentally different from these large scale AI systems. Those types of AI systems, they're task specific, they're often very, very small and cost extremely small amounts of energy to develop. They're trained on highly curated data sets that do not require the type of labor exploitation and content moderation that goes into something like ChatGPT and they have already documented, we know that when we build these systems we get benefits on the end rather than this speculative, maybe in the future we'll reach AGI one day and it'll solve everything. And so once you kind of realize that, once you realize there's actually a portfolio of different options for the shape of AI and what it can do, it suddenly becomes blatantly obvious that we're actually in this colossal capital misallocation problem where we're putting all of our capital in the one type of AI that has the absolute worst trade offs. And we should be rapidly urgently shifting that capital to all of the other types of AI that have the correct trade offs, very little cost for maximal benefit.
- [31:40]
Interviewer (Adam Lowenstein)
The question of scale or the idea or the obsession with scale, I guess you describe as a doctrine in Silicon Valley and in these companies that the only way to do this, as you're just referencing, is to scale as big and as fast as possible. And something I see a lot in headlines these days in press releases is talk of hyperscaling and mega campuses and all of this stuff, which is obviously touted as a good thing when you see hyperscale and megacampus and where bigger is better. So we must be doing something revolutionary and profitable. But it seems like the biggest, certainly from an environmental perspective, the biggest costs come from the scale. Right. It's not necessarily the technology itself, but the size at which that they are obsessed with doing this stuff. Is that right?
- [32:30]
Adam Lowenstein
Yeah, exactly. That is my fundamental critique about Silicon Valley's approach to AI. They've created this idea that you can no longer challenge within the Valley, that in order to reach some kind of utopic state through the creation of AGI, you just have to pour ever more data into these models and train them on ever larger supercomputers. And we are now talking about supercomputers the size of Manhattan. Meta and OpenAI have both drafted plans to build supercomputers the size of and that consume the same power demands as Manhattan. This is not actually scientifically sound. You know, like when I had the privilege of starting to cover AI research, well before ChatGPT came out and well before large language models became the obsession, AI research was actually heading in the exact opposite direction at the time. People were looking to build smaller and smaller AI models. And it was all about tiny AI, because there were all of these different techniques that researchers were experimenting with that found that you can build really powerful AI systems with minimal amounts of data and also on pocket, like a phone, like your pocket computer. And that kind of understanding that we can actually create new algorithms, create new training techniques, just redesign AI systems from the ground up to use less and less resources. Something that's been totally thrown out the window by Silicon Valley. And it like, does not make sense to me why we have gotten stuck in. Well, I mean, it does because the people that are putting us on this map have an extraordinary amount of capital, extraordinary amount of narrative power and so on. But yeah, it's not scientifically or technically justified and it has gotten us into this absolutely twisted state where we are burning down the earth in order to do something that's wholly unnecessary.
- [34:33]
Interviewer (Adam Lowenstein)
And I keep coming back to the psychology and the worldview of the people making these decisions. Because talking about social, environmental, political, cultural trends, you know, we often talk for good reason about problems that are systemic and structural rather than individual. But I feel like this is one of those cases where it is all those things, but it's also very individual in the sense that so few people are, are making these decisions that are impacting so many of us. And I'm just wondering because you've spent so much time with folks at current former employees at OpenAI as well as the other companies, and there's obviously a lot of churn between them, how much do you think this trajectory that we're on, from pocket sized AI half a decade ago to Manhattan sized supercomputers potentially in the near future, how much of that do you think is driven by just individual desire for wealth and more specifically power and domination versus actually wanting to believing in their hearts that these technologies will solve the problems that they claim to be able to solve. I'm just wondering how you think about the psychology at play there and how much of our future is being dictated by a really small number of people's desire for domination over the rest of us.
- [35:58]
Adam Lowenstein
Yeah, I think the best way to answer this question is I think in order to be one of these people you have to be self delusional. And so I'm sure that they believe that they believe that they're doing this because out of goodness. I don't think you can sustain waking up every morning and orchestrating these deals and decisions that are terraforming the earth and reshaping geopolitics and rewiring everything in these ways without deluding yourself into believing that you are on a mission for the benefit of all humanity. And I think that was not something I fully understood until I reported my book and spoke with so many people in this world was. I did think that there was more distance between the rhetoric that they use publicly to leverage whatever public opinion or their political capital or narratives to get what they wanted and their actual true beliefs. And what I realized the more that I reported is actually the rhetoric and what they believe. The distance collapses over time because you, you just cannot continue to say all of these things and do all of these things without giving telling yourself that that is true, that is your truth. People's beliefs become molded by what they need to accumulate more power and accumulate more wealth. You know, I had the. Because I started reporting on OpenAI several years before ChatGPT came out. Like I, I interviewed people back then that I'd been interviewed, re interviewed for the book. So I, I sort of have seen people transition in their beliefs over time as they've become more and more part of the company and, and, and this world. And it really does completely transform them and who, who they think they are and what their worldviews are. Like I was talking to people back then who were like, I don't really believe in the AGI thing, but you know, I just get, I get a good salary, I get a lot of resources to play around with cutting edge research. It's basically like working in academia, but just like way better funded who have then now become complete AGI believers. Like do not even question for a second that they are building something that could be akin to a God and will have utopic qualities and that this is the reason that they were brought to this earth.
- [38:42]
Interviewer (Adam Lowenstein)
I'm sure it's intoxicating to feel that. I can see how people might get addicted to that feeling of being on some sort of divine mission.
- [38:52]
Adam Lowenstein
Yeah, absolutely. And not just a divine mission. Like people also get addicted to just the sheer, I mean they get addicted to a lot of things. They get addicted to the sheer size of the resources they can have access to. They get addicted to the amount of influence that they can have. You know, like I've had people say to me, well, there's really very few other companies that you can work to have ripple effects on billions of people around the world. And for them, that is, they're not saying that in a Machiavellian way. They're saying that in I want to change the world to be a better place. So what better leverage can I get than being at a company that touches billions of people's lives? Like they're saying it from a place of this is, how could you not let take that opportunity? If you like, if you wanted to change the world and you stepped into my shoes, wouldn't you do the same thing?
- [39:50]
Interviewer (Adam Lowenstein)
It's really unsettling to think about.
- [39:53]
Adam Lowenstein
Yeah, it's, it totally the realization that the self delusion is that strong. Writing the book really made me feel a lot more freaked out about where we could be heading if we don't as a society rise up to contain the empire of AI.
- [40:18]
Interviewer (Adam Lowenstein)
Yeah, I mean it just shows why empire is really the perfect description for what is happening. Was there a point when you were reporting the book or when you were writing it when that became clear to you? That this was the project they were undertaking was the construction of not just a company or a conglomerate, but an empire.
- [40:39]
Adam Lowenstein
So interestingly, when I first started working on this book, it had very little to do with OpenAI and only to do with the AI industry as an empire. And the reason is because I had been working on a project called AI Colonialism for MIT Technology Review just a year before ChatGPT came out. And I'd already been thinking about the parallels between the colonialism and the way that the AI industry was operating around the world. And this was based in part on me reading a bunch of scholarship that I already identified these parallels and then growing really fascinated by it and looking to see whether or not that was actually happening in the real world and traveling to different countries to document those parallels and finding extremely striking parallels in the process. And so I had originally conceived of the book as just let me just write more about that, about the argument that there is something very neocolonial happening here with Silicon Valley's push to build and deploy this technology. And then when ChatGPT came out, my agent was actually the one that said, well, how does this change things? Do you think that's fixed the problems? And I was like, no, it's made it way worse, like orders of magnitude worse. Because now they've fired the first shot where every single company is now going to go after scale the way that OpenAI has religiously done, which was not at all the norm before then. And that's going to accelerate the resource extraction, accelerate the labor exploitation, accelerate the environmental degradation in all of the ways that I was already seeing those parallels to the empire. And so, yeah, so the revolution went the other way around. It was starting with empire and then realizing that OpenAI was the center of so much of this story, rather than starting with OpenAI and then realizing they were an empire.
- [42:44]
Interviewer (Adam Lowenstein)
Something you point out throughout the book is the way that OpenAI sets the precedent for the way the rest of the industry goes. Certainly the obsession with scale, as you mentioned. Another one is the kind of rapid evolution or devolution from these being essentially research hubs doing peer reviewed research. And yes, they're funded by private industry, but everything's very open, very academic, lots of collaboration with universities and scholars to, in another parallel to the fossil fuel industry, very secretive. They have the information about what these things do as best as anyone does, but they're not publishing it, they're not sharing it. Critical research gets suffocated, people get fired for criticizing the regime. Can you talk about the Suppression of inconvenient information and how fast that shift occurred from we're essentially private research hubs to this is proprietary information and do not deviate from the narrative.
- [43:44]
Adam Lowenstein
Yeah, so I think people who started becoming aware of the AI industry and its practices post ChatGPT would think it's perfectly normal that these companies are very secretive about their intellectual property and any kind of AI research would be considered intellectual property. And therefore it's not weird to them that these companies are tight fisted about that kind of information and not transparent. For people who knew what the norms were in AI research before ChatGPT, this is a dramatic 180 shift. Before, even though much of the tech industry was bankrolling AI research, the understanding was that in order to be competitive in attracting talent, you had to entice AI researchers by promising them that they would ultimately get to publish all of their work in public. Because AI research was still very academically driven. And so even if you were a Google researcher or a meta researcher or whatever, your street cred was still based on how many papers are you publishing in top publications, how many citations are they getting? It was just like the credentialing was just very, very academically coded, I guess you could say. OpenAI. Not only did they close themselves off, in a great irony to their name, they closed the entire industry off by doing a lot of work early on. To see this idea that maybe opening up a lot of this AI research could be dangerous and therefore it was actually the responsible thing to shutter this research so that quote unquote, bad actors could not get access to it. And that created a cascading effect across the industry where suddenly, when it became clear to companies that they could still retain the top researchers and be competitive in the talent race while being closed off, then it became sort of like dead obvious to all of them that that was the best business decision, is you want to keep your competitive advantage close to your chest and not share that information. And so what we've seen happen is very quickly, because structurally most AI researchers were already employed by big tech. Suddenly the majority of the research discipline now becomes distorted based on what companies think is appropriate or not appropriate for the public to know. And so it's not actually a science anymore. I mean, it's just prior and we have an absolute, completely inaccurate understanding now of what the true capabilities and limitations of these AI systems really are. Because you cannot audit what these companies claim the AI systems can do without any of the transparency on how they were built, what data were they trained on, what kind of tests are being run on them, what contexts have they been stress tested in, and so on.
- [47:04]
Interviewer (Adam Lowenstein)
And that's true for some of the environmental impacts in carbon emissions too, right? It's hard to understand the true impact without them revealing some of this information.
- [47:14]
Adam Lowenstein
Yeah, exactly. So we don't know how much energy it takes to train a model. I mean, of course there are open source models and there's been plenty of. Well, I shouldn't say plenty. There has been some really fantastic research on using open source models as a proxy for understanding the energy and environmental impacts of training these large scale AI systems. But we only know what the real impacts of the commercial closed source systems are when companies deem it okay to release that information, which has been very rare, but has happened when they've come under extreme public pressure to do so. So Google has over time slowly dribbled out some information about the environmental impacts of its models and Meta has tried to also do a little bit of that to try and generate some good PR around their transparency and trying to position themselves as sort of like an open source leader. But it is so limited and the transparency is completely disproportional to what is actually needed based on the size of the environmental impact and energy consumption.
- [48:29]
Interviewer (Adam Lowenstein)
There was something that you noted at some point in the book, you made the. When I read it, it seemed very obvious, but I hadn't thought about it at all. The point that to solve a global challenge like the climate crisis, again, whatever solve means we'll also need more social cohesion and global cooperation. And of course that is precisely what these empires are undermining. I guess I had been thinking about it as the way they wanted me to think about it in some ways as a technology. Could you just unpack that a little bit? The way that these empires are undermining the very cohesion and cooperation that we would need to actually make progress.
- [49:11]
Adam Lowenstein
Yeah, this is something that has been sort of a revelation that I've had again and again and again in reporting on technology is that so often as a society we are vulnerable to believing that technology will solve social problems and actually only social solutions will solve social problems. And ultimately climate change at this point is not a technology problem. In fact, we have an abundance of solutions that we could be deploying and it's just a lack of political will, it's a lack of global cooperation, a lack of all of these soft skills that have caused us to fail at actually getting there. There's this organization called Climate Change AI that I really love. It's A nonprofit that was set up by a bunch of AI researchers around the world to think deeply about how do we actually, what can AI actually do to try and mitigate climate change. And they document this long list in a white paper of all of these different computational challenges. Because ultimately AI is a computational challenge technology that lends itself to computational challenges. So it documents all these computational challenges that could be helpful for solving when it comes to climate change mitigation, like integrating more renewable energy into the grid, more accurate weather prediction, more accurate climate disaster prediction, reducing the energy demands of buildings and cities. And then in the white paper it says ultimately it's not just these technologies that are going to get us there. Because these techno like they list, all the AI techniques that they list have absolutely nothing to do with large scale AI generative AI systems. They're all techniques that have been around for basically a decade. And they were like, that is evidence enough to show you that it's not actually a technical problem at the end of the day. And so that was kind of what I was getting at in that line is like these companies are creating AI systems currently that are straining resources, which heats up geopolitical competition over those resources. They are perpetuating an arms race narrative that also erodes the willingness of different geopolitical powers to cooperate with one another. They are creating machines of misinformation and disinformation that's eroding the fabric of trust in various societies that is also the building block for cohesion and cooperation. And so they're kind of based like when you start to realize it, that climate change isn't really a technology problem and it is a social problem. All of the things that we need to fortify are actually being chipped away at, maybe not chipped away like hacked away by the industry with the current systems that they're building.
- [52:10]
Interviewer (Adam Lowenstein)
There's a very hopeful point that you make in a couple places throughout the book, which is that despite the power that these empires have, they're not entirely invulnerable. Could you share one of the stories of some of the communities that have successfully fought back? I was particularly moved, by the way, in response to some of these companies trying to come into communities in Chile or elsewhere under the secrecy of shell companies trying to sneak in a massive data center that's going to use up all the water in an already drought stricken part of the world. People see what's going on and they mobilize and they have had some really inspiring successes.
- [52:51]
Adam Lowenstein
Yeah. So one reason I also think the empire Analogy is extremely pertinent is because empires are made to feel inevitable, and yet they've always fallen in history. And it's because their foundations are extremely weak. You cannot actually ultimately sustain this degree of extractivism and exploitation at such a large scale without people revolting. And that is what I document happening in Chile, where Chile has a very long history of extractivism. Extractivism being, you know, a concept that came out of decolonial scholars from Latin America talking about the harvesting of their resources for the benefit of people far away rather than the local community. And they essentially see the AI industry and all the data centers and the mining that the industry is doing to try and build these colossal silicon monstrosities as just an extension of this history. Yet again, we are dealing with a greedy industry trying to extract at scale our precious earth. And so they immediately became activated when they discovered that this was happening. And I spoke with these activists in this community right on the outskirts of Santiago called Cerrillos that was. They learned that Google was trying to build a data center in the one town that actually has access to a public drinking water source. Because in Chile, due to its history of dictatorship, most things were privatized, including water. But the one municipality that had a free public drinking water resource was the municipality that Google then was like, yep, we're going to put our data center in there and then tap into this freshwater resource and use to cool our facilities. And this community lit up and was like, absolutely not. These activists started knocking on all of the neighbors doors, posting flyers, creating memes and art, political art and all this stuff to educate their neighbors that this project is not at all going to benefit our community and is in fact taking the one extremely precious resource that we have, to your point, in a drought stricken time. And they made so much noise that escalated all the way to both Google's headquarters in Mountain View and to the national Chilean government. And basically, after extraordinary pressure where they've stalled this project for five years, the Chilean government has now created a roundtable for consulting residents and environmental activists on their data center plans and putting them in conversation with companies like Google and Microsoft. And it's not a perfect solution in that the activists have said, you know, the moment that they blink, everything can fall apart. And so they have to continue being vigilant, they have to continue protesting, resisting, being on the streets. But it is a remarkable step that they got the government to make to even bring them to the table and is just a lesson to be learned by everyone around the world that if you remember that you actually still have agency. You can absolutely shape the trajectory of AI development by loudly, forcefully making that kind of trouble when these companies are engaging in this imperial activity.
- [56:32]
Interviewer (Adam Lowenstein)
Such a good note to end on. Thanks so much for this conversation, Karen, and for what is truly it's such an important piece of work and scholarship, so I am grateful for the enormous amount of time that went into it.
- [56:46]
Adam Lowenstein
Thank you so much for having me. Adam.
- [56:53]
Amy Westervelt
Drilled is an original Critical Frequency production. This episode was reported and written by Adam Lowenstein and produced by Peter Duff. Artwork for Drilled is by Matt Fleming. Fact checking by Naomi Barr. Our First Amendment attorney is James Wheaton with the First Amendment Project. Drilled is distributed by Pushkin Industries. Huge thanks to the team there, including Greta Cohen, Eric Sandler, Grace Ross, Morgan Ratner, Owen Miller, Kira Posey, Jordan McMillan, Brian Schrebrneck, and Jake Flanagan. You can find a written version of this interview and lots of other author interviews, stories and all kinds of content on our website at Drilled Media. You can also sign up for our newsletter there and follow us on all the social media sites.
- [57:43]
Adam Lowenstein
Drilled Media.
- [57:44]
Amy Westervelt
Thanks for listening and we'll see you next time.
- [57:52]
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What?
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