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A lot of AI technology may not work very well, but providing consumers with reliable information was never its major commercial promise. Investors have poured billions into generative AI because of the promise that it will eliminate jobs on a massive scale. Tech journalist Brian Merchant joins Movement Memos host Kelly Hayes to discuss how the AI boom is being used to displace workers, degrade information, expand surveillance and strengthen state violence—and why this brittle corporate project can be disrupted.

Music: Son Monarcas, Mizlow, and Daniel Fridell

Note: This a rush transcript and has been lightly edited for clarity. Copy may not be in its final form.

Kelly Hayes: Welcome to “Movement Memos,” a Truthout podcast about organizing, solidarity, and the work of making change. I’m your host, writer and organizer Kelly Hayes.

What happens when a technology doesn’t have to work particularly well to remake the world? Today, we’re talking about AI in the workplace, Google’s decision to ruin its search engine, robotaxis getting people arrested, Flock cameras getting destroyed, the movement against data centers, and what it means to build power against the tech industry.

No Abandonment, No Bunkers: Preparing for Disaster Together

My guest is my friend Brian Merchant, author of Blood in the Machine and creator of the newsletter and podcast of the same name. The AI boom is often presented as an unstoppable technological shift, but Brian’s reporting reminds us that it is a brittle and faulty corporate project — and that corporate projects can be disrupted.

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Kelly Hayes: Brian Merchant, welcome back to “Movement Memos.”

Brian Merchant: So good to be back. Thanks, Kelly.

Kelly Hayes: How are you doing today?

Brian Merchant: I’m hanging in there. There’s a lot going on, there’s always a lot going on these days, and I’m a little bit hot because I am in Europe right now, where the heat wave is just receding. But aside from all those small things, I am doing well, thank you. How are you?

Kelly Hayes: Well, I am in Chicago, where another heat wave is rolling through, and the air here is terrible right now. So, I’m just going to hide out in my apartment and talk to you and feel good about that.

Brian Merchant: Sounds like there’s some kind of a theme developing here with the heat, and, you know.

Kelly Hayes: There might be something going on there.

Brian Merchant: Too early to say for sure, but yeah, I think let’s circle back to that. Let’s come back to that one.

Kelly Hayes: Huge if true.

So, Brian, a lot of people are familiar with your work, and some of our listeners will remember you from the last time we were in conversation, but for the unacquainted, what would you like people to know about who you are and where you’re coming from?

Brian Merchant: Yeah, I think, I guess most pertinent to what we will be discussing today is that I am a longtime tech reporter and tech writer, a journalist, and author of a book called Blood in the Machine, which is about the history of industrial automation, and what we can learn about it today. And I’ve been writing about that sort of framework, using that framework and applying it to AI, and this most recent surge of corporate automation that we’re seeing handed down from Silicon Valley, and what’s happening to labor on the ground, and I write about that at my newsletter, Blood in the Machine.

Kelly Hayes: And you also have a new podcast connected to that newsletter.

Brian Merchant: I do, yeah. It’s something that’s still early days, thank you for shouting it. My producer would be quite glad that you did. Yeah, it’s an audio component, it’s something that folks have been asking for for a little bit, and I’m hoping to host organizers in the fight against data centers, organizers who are trying to confront AI in the workplace, people whose jobs have been impacted by AI, authors, journalists, documenting this stuff in the front lines. So, yes, that’s the latest endeavor. At time of recording, our last guest was a participant in the Summer of Ludd activities in New York City, which was a big anti-big tech weeklong slate of programming, protests, and affairs. So, that might be a good one for folks of “Movement Memos” to check out.

Kelly Hayes: I really appreciated that conversation, and I’m excited about this podcast. It’s only been around for a few episodes now, and I am looking forward to keeping up with it. So, I hope folks will check it out.

Brian Merchant: Yeah, thank you.

Kelly Hayes: To give people a general overview of where we are in our experience of the harm and hype of AI, for a long time there’s been a talk of a bubble, we’ve seen a lot of AI use cases fail, a lot of people pushed out of their jobs, or forced to do their jobs in ways that are harmful or simply don’t make sense, and even some people fired and then rehired. Given all of that, what is the current state of so-called artificial intelligence and our relationship to it?

Brian Merchant: We were chatting a little bit before we started recording, and the word “messy” came up, and I’m going to go with messy. The state of affairs is a complete mess right now. It is incredibly in flux. So, as just a little bit of background, so ChatGPT, most people are likely aware on some level, really blew up at the end of 2022, it spurred this rapid-fire development, investment, and commercialization cycle that saw AI, generative AI, what we now think of as AI, as a product, as a technological trajectory, take shape. So, it’s really been the last three and a half years. And things have gone hyper speed in terms of the industry’s ramping up, again, investment in this technology, and turning it into the slate of products that are now inescapable today on your app store, on Google, on just about everywhere else.

And so, the largest thrust behind all of this, sure the chatbot was a flashy tech demo, and a lot of people were interested in using it for that reason, as a consumer product. But we have to bear in mind that there hasn’t really been any serious monetization there. And in fact, there’s a lot of reason to believe that investors were never really as excited about, say ChatGPT, the chatbot, as they were about this promise that has undergirded the entire AI development boom, which has been this promise that AI can replace labor, that it can replace jobs. That is, according to my analysis anyways, according to my understanding of the cycles of history, and the industrial development, and how these technologies are developed and sold.

And if you look at, for example, OpenAI’s charter, where it says its goal is to build AGI, or an artificial general intelligence, and it explicitly says that it explicitly defines AGI as something that will replace most meaningful work. And so, that is a direct sales pitch to investors, and it has been for now three years and counting. And so, whether or not we see success — and you mentioned that there’s been a lot of hiring, firing, rehiring, and a lot of questions and turbulence in the AI world — but we have to remember that, number one, undergirding this entire adventure from Silicon Valley is the promise that it will soon be able to eliminate all jobs. And so, there are a lot of executives that have bought into that, have believed it, there’s been a lot of pundits who believe it, there’s been a lot of middle managers who believe it.

And so, we have already seen a lot of disruption. We’ve seen tons of layoffs in the tech sector, particularly, layoffs in other sectors, we’ve seen hiring slow down among those looking for entry-level jobs, and we’ve seen creative fields in particular impacted by generative AI’s rise, in situations where you can produce an image or some text, or if it’s a job … Translators, illustrators, folks like that are actually being hit economically hard. So, this whole messy picture is still somewhat up in the air, there are a lot of unanswered questions, there are a lot of things that we still need to wait to see how they’ll shake out in the long run. And whether or not AI ends up being capable of replacing a lot of these jobs is one of those large questions that’s still looming.

But what’s important for our purposes is to know that that is the logic that has been imbued in this technology from the beginning. It’s an enterprise automation product above all, in terms of what companies are hoping to see in terms of cost savings and value created, obvious value stores. There are a lot of other harmful things that AI does, and a lot of other issues with AI, but in the labor picture, that’s the big one. It’s being sold as an automation technology. And three years in, there’s still intense debate over what it can and cannot do. But as folks who are thinking about this stuff’s impact on the workplace, and what we should be keeping in mind, it’s that your boss is always going to use this as leverage to push against workers to say: Well, maybe AI can be used to replace your job, so don’t ask for a raise. Maybe we’ll see if we can automate X, Y, and Z jobs, and then if we can’t, maybe we can hire back some contract labor to cut some costs. Let’s see if we can use AI instead of hiring an illustrator because it’s so, so, so much cheaper, and we’ll see if the client balks and if there’s any issues down the line.

So, we’re in this period where there’s a lot of negotiation going on, like, how far can we push our AI use without clients rebelling, without screwing up too much stuff … Because AI still gets things wrong quite a bit of the time. How much tolerance is there in the system for unfettered AI use? How much cost savings can we realize by using this stuff without completely tanking our products, tanking our workplace, and … without leaving some permanent damage?

Kelly Hayes: You recently did an episode about Google doubling down on its effort to rebuild Search around Gemini. What are the broader implications of that move, given how dependent so many of us are on Google Search?

Brian Merchant: Yeah, it’s a really good example. I’m glad you brought that up because it’s at the forefront of what’s happening with AI, and in a lot of ways it encapsulates that sort of push. Cory Doctorow famously calls it “enshittification,” I’m sure a lot of listeners have heard that term. But that’s what goes hand in hand with a lot of this job automation. And it’s not just job automation, it’s the automation of other digital features. And again, seeing what we can do with AI for cheap, that we can get away with, and hopefully eventually cut some costs down. Again, I should mention the caveat that finding those cost savings and finding big ones is especially imperative because AI is just, as a lot of you might know, is so expensive to run and to operate. It just requires tons of data, tons of energy, tons of salary cost to hire talent for these things. So, it’s just huge enormous costs to run AI. And so, the desire for these companies to find those cost savings is now accelerating.

So, all that said, Google has decided to, as you said, transform its search product, and in a very aggressive way, a way that 10 years ago even would’ve been completely unthinkable. So, many of us may know that if we use Google search now instead of getting an indexed list of search results, we get Google’s AI overview, which is an AI generated answer based on the query that we made. And it’s the AI’s best shot at just answering that question with the intent of keeping us on the page, instead of clicking through to a link that would take us off of Google, and onto say independent writers, or a newspaper’s website, or a small business’s website, or you name it.

And so, this shift is really, to me, showing what AI is all about. And I think it’s one that for folks like Kelly and I, is especially close to home. So, what it’s doing is it’s indexing our websites, and anything that we may have written, just taking that material, incorporating it into its data set, and then if we search for, “How is AI impacting jobs?” When before maybe it would send a link to Blood in the Machine, or, “What is the state of on-the-ground organizing?” And maybe it would’ve pulled a nice essay from Organizing My Thoughts, now it just spits that information out onto Google’s own platform, onto where Search used to be. And so, it’s transmuting all of this creative independent labor into a paste that Google can sell because Google does sell it.

It does put ads right underneath that new answer paste that, oh, by the way, along with the information gleaned from our websites, it also is putting falsehoods in there at a rate of one out of every 10 searches — or it’s wrong 10 percent of the time, is still the finding. It still hallucinates, as the AI researchers call it, 10 percent of the time. So, it’s generating this absolute mishmash of information that Google is hoping that it can profit from by selling more ads against, essentially, our labor. It’s taking that work and that effort and that information that was generated by other parties, moving it over onto Google’s side of the ledger, and then Google’s monetizing it and selling that information.

And again, the question is: Can it get away with that? Well, is AI Overview, Google’s product, good enough, or will users begin to revolt? Sadly, right now, it doesn’t seem like they are revolting in large numbers, they are just adapting to this new era in which Google is wrong part of the time. And we can talk about some of the things that are happening in that sphere that there are actually cases going, especially in Europe, there’s a recent court case in Germany, where the court found Google liable for presenting false information, and now Google might have to face up to the fact that it is spouting not just incorrect, but potentially harmful, even defamatory information. And so, if Google’s held liable for doing that, if you think about Google’s billion searches a day, or whatever it is at a given time, and then 10 percent of that is wrong, and then even 10 percent of that is harmful or defamatory, that’ll add up fast.

So, that may be one check on this particular trajectory that Google has. But that is to say, Google is the biggest tech company that is going all in on AI. All the tech companies are investing and going in on AI on different levels, but Google is probably doing it the most, and it is transforming its key product most aggressively, and pushing AI out to the front of it. And so, it is, I think, the biggest company to watch in terms of how that fares. Legally speaking, what the impacts are socially — again, we talked about the impact on independent creators, I briefly touched on the impact on mass information quality degradation … Again, if you think about 10 percent of all the information that you get from Google, or you used to get from Google, is now wrong, it’s just creating this world where the “truthiness,” to use that old lib term, is omnipresent now.

I think our ability to really discern what is accurate and what’s not, what’s true and what’s not is hindered. And certainly journalism and folks who try to make a living creating good information are hindered yet again. It’s been a rough 20 or so years for journalists, independent or legacy, and this is just yet another slide down the slope.

Kelly Hayes: A couple of things come up for me as I hear you say this. One is what people sometimes call the Elon Musk effect: the way Elon Musk can seem like some kind of genius—or, at least, I think more people used to see him that way—until he starts talking about something you actually know about.

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