A Simple Test to See How Ready You Are to Fight Fascism
Hagen Blix, co-author of "Why We Fear AI" joins BJ to talk about how it's not artificial intelligence you need to be afraid of, it's the billionaires. And our host, Rosie Tran, covers how to protect yourself from Bluetooth Trackers like Apple Airtags
Rough week, huh?
I know.
But do you want to hear something really funny? People are starting to call Meta’s Ray-Bans “pervert glasses.” According to Futurism, one person suggested calling them “Mark Zuckerberg’s pervert glasses.” Personally, I think “Mark Zuckerberg’s Pervert Machine” would be pretty funny, too. But “pervert glasses” is brilliant.
Going forward, that’s how we at Stupid Sexy Privacy will refer to any eyewear with a built‑in camera. I hope you do the same. Not only is it funny, it also makes your friends and neighbors aware of the danger those glasses pose.
You’ve got ICE agents right now taking pictures of people’s faces and cross‑checking them in an app called Mobile Fortify. We don’t know what they’re doing with all that data, but it’s safe to say it isn’t for sending out Christmas cards.
So: do you really think now is a good time to be wearing pervert glasses and helping out ICE? We don’t.
That said, before we get to today’s episode with Hagen Blix, co-author of Why We Fear AI, we wanted to address something quickly.
Either Everyone Counts or Nobody Counts
I was talking to someone recently about how their coalition is fracturing. They said this because some people object to the concept that “all people are entitled to equal treatment under the law.” Despite the fact that, here in America, the 14th Amendment and our Constitution applies to all people within the United States. Not just citizens.
So. I have to say: if you’re in a group with people who don’t believe everyone should be treated equally, you’re in the wrong group. Everyone counts or nobody counts. Put another way, the laws apply to all of us equally, or they don’t apply at all.
Another thought: if your group fractures at the first sign of trouble, you don’t have much of a group at all.
Here is a simple test of how ready you are to fight fascism: have you recruited 10 neighbors for your local Signal group?
If the answer is no, you’re not ready.
Not every neighbor will want to join. Not every neighbor should be trusted. But you should start forming these groups and talking about who needs what and how you can help one another.
Signal Groups are also a great way to address misinformation and disinformation that may be circulating within your community.
So if you’re watching the news and freaking out, this is something you can do right now that’s local, tactical and beneficial in the long run for taking our planet back from authoritarians and the billionaires who fund them.
If you want to learn more about setting up a neighborhood Signal group, start here.
-BJ
Hello. Farewell. Hello. Farewell.
You can follow me here on Bluesky
Stupid Sexy Privacy Show Notes For Season 1, Episode 28
Episode Title: Body Cameras, Like Communism, Only Work In Theory
Guests: Hagen Blix, co-author of "Why We Fear AI"
Episode Summary: Hagen Blix, co-author of "Why We Fear AI" joins BJ Mendelson to talk about how it's not artificial intelligence you need to be afraid of, it's the billionaires using AI to push their vision of the world on you. And our host, Rosie Tran, provides a season two preview, while covering how to protect yourself from Bluetooth Trackers like Apple Airtags. She also explains why tariffs, like body cameras, don't work anywhere near as well as politicians want us to think.
Resources (NO Affiliate Links. This is what we use.)
Our Sponsor: DuckDuckGo <--Our Recommended Browser and VPN
Get Your Privacy Notebook: Get your Leuchtturm1917 notebook here.
-BitWarden.com (Password Manager: easier to use, costs money)
- KeepPassXC (Password Manager: free, harder to use, but more secure)
-Slnt Privacy Stickers for Phones and Laptops
-Slnt Faraday bag for your Stranger Danger phone.
-BitDefender (best anti-virus for most people across most devices)
-Stop using SMS and WhatsApp, start using Signal.
-Use Element instead of Slack for group coordination
-Use StopGenAI's Guide to getting Generative AI out of your life.
--Use cash whenever possible. If you have to buy something online, try to use Privacy.com to shield your actual credit or debit card when making purchases online.
Get In Touch: You can contact us here
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Season 1, Episode 28: Body Cameras, Like Communism, Only Work In Theory
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Stupid Sexy Privacy Intro
Rosie: Welcome to another edition of Stupid Sexy Privacy.
Andrew: A podcast miniseries sponsored by our friends at DuckDuckGo.
Rosie: I’m your host, Rosie Tran.
You may have seen me on Rosie Tran Presents, which is now available on Amazon Prime.
Andrew: And I’m your co-producer, Andrew VanVoorhis. With us, as always, is Bonzo the Snow Monkey.
Bonzo: Monkey sound!
Rosie: I’m pretty sure that’s not what a Japanese Macaque sounds like.
Andrew: Oh it’s not. Not even close.
Rosie: Let’s hope there aren’t any zooologists listening.
Bonzo: Monkey Sound!
Rosie: Ok. I’m ALSO pretty sure that’s not what a Snow Monkey sounds like.
*Clear hers throat*
Rosie: Over the course of this miniseries, we’re going to offer you short, actionable tips to protect your data, your privacy, and yourself from fascists and weirdos.
These tips were sourced by our fearless leader — he really hates when we call him that — BJ Mendelson.
Episodes 1 through 33 were written a couple of years ago.
But since a lot of that advice is still relevant, we thought it would be worth sharing again for those who missed it.
Andrew: And if you have heard these episodes before, you should know we’ve gone back and updated a bunch of them.
Even adding some brand new interviews and privacy tips along the way.
Rosie: That’s right. So before we get into today’s episode, make sure you visit StupidSexyPrivacy.com and subscribe to our newsletter.
Andrew: This way you can get updates on the show, and be the first to know when new episodes are released in 2026.
Rosie: And if you sign-up for the newsletter, you’ll also get a free pdf and mp3 copy of BJ and Amanda King’s new book, “How to Protect Yourself From Fascists & Weirdos.” All you have to do is visit StupidSexyPrivacy.com
Andrew: StupidSexyPrivacy.com
Rosie: That’s what I just said. StupidSexyPrivacy.com
Andrew: I know, but repetition is the key to success. You know what else is?
Rosie: What?
Bonzo: Another, different, monkey sound!
Rosie: I’m really glad this show isn’t on YouTube, because they’d pull it down like, immediately.
Andrew: I know. Google sucks.
Rosie: And on that note, let’s get to today’s privacy tip!
This Week's Privacy Tip
Rosie: Hey Friends, it's Rosie Tran, and this week you're getting a brand new privacy tip and interview. This one featuring Hagen Blix, the co-author of Why We Fear AI: On the Interpretation of Nightmares.
We thought this interview would be a nice follow-up to last week's interview with Dr. Uri Gal.
But before we get to Hagen's interview, we wanted to tie up some loose ends.
Season one of Stupid Sexy Privacy will end on April 16th. The all new second season will debut on April 23rd.
The following are some leftover items we wanted to make sure we covered before this season ends.
- Something we're hearing a lot from people is how organized they are. And then of course, when we ask them a few questions, we find out they're not organized at all.
So. Here is a simple test everyone can use to figure out if they are organized: Do you have, right now, ten of your neighbors in a Signal Group chat? If the answer is no. You're not organized.
What you have instead is probably a loosely affiliated group of people. One that will fall apart at the first sign of trouble. If you missed BJ's Burner Phone 101 presentation, where we discussed the neighborhood Signal groups, we encourage you to go back and listen to that episode.
Season 1 of Stupid Sexy Privacy was all about how to protect yourself from fascists and weirdos.
Season 2 is all about how to fight the fascists and weirdos.
So that Burner Phone 101 episode is a preview of what's coming next.
- This one makes us crazy, but a lot of people still don't know how Tariffs work. So we just want to stress that a tariff is a tax that YOU pay. YOU are paying it. You. Nobody else. Not Canada. Not Mexico. Not China. And according to Axios, you and I are each owed — at the time of this recording — about $1,700. That's how much extra you and I paid since January 20th of 2025 on groceries and everything else because of these tariffs.
- Body cameras, like Communism, work in theory. In theory, a law enforcement agent wearing a body camera is a great idea. But right now, law enforcement frequently turn off those cameras, rendering them useless. So asking ICE agents to wear body cameras — when a bunch of them had body cameras on when they murdered Alex Pretti and Renee Good — is about as stupid as the tariffs. The only way to reign in ICE is to abolish ICE. That's what everyone should be demanding right now.
- Remember that you always have a choice. It's very easy to feel overwhelmed. That's a tactic used by authoritarians all over the world. They want you to feel like there's nothing you can do. But there's always something you can do.
For example, this is the number for the US Capitol Switchboard: (202) 224-3121.
You can call that number, and ask to be connected to your senators and to your House representatives. Tell these people what's on your mind.
Like how all $75 billion taken from Medicaid and SNAP, to fund ICE, should be put back into Medicaid and SNAP. That's a thing you can do. Right now. Because we'll tell you a secret. Politicians, no matter the political party, are cowards. If enough people call to yell at them, they'll remember who the boss is, and that boss is you. Not them.
And while it's true one call may not make a difference, if a bunch of people start calling? Or if you start calling every week? That makes all the difference in the world. Volume and momentum is what counts. A point we will return to in Season 2.
- Ok, last but not least. We recently ran our "how to stay safe while going out on a date" episode. There was just one thing we wanted to add that isn't discussed during that episode, which are Bluetooth Trackers. Stuff like Apple AirTags, basically. The question being, what do you do if someone plants one of these trackers on you?
We're going to give you two options:
This is the official Apple version of what to do, and for android users, you can download an app released by Apple called "Tracker Detect."
But If you have an iPhone, you want to make sure the software on your phone is up to date, and then go to Settings, tap Privacy & Security, and select Location Services. Then, there are some additional steps you need to take. They are as follows:
- Turn Location Services on.
- Scroll down and tap System Services, then turn Significant Locations on to be notified when you arrive at a significant location, such as your sex dungeon in Columbus, Ohio.
- Go to Settings, then tap Bluetooth. Turn on Bluetooth.
- Then Go back to Settings, tap Notifications, then tap Tracking Notifications. Turn on Allow Notifications.
- Finally, Turn off Airplane Mode. If your device is in Airplane Mode, you won't receive tracking notifications.
Following these steps will help you spot any device tracking you using Bluetooth.
Apple also provides official documentation on how to find the serial number of the air tag tracking you, which you can then report to the police. We've included links in today's show notes on how to find the serial number, and how to disable the battery inside the Airtag. You want to disable the battery after you've identified the serial number.
From Apple: How to replace the battery in your AirTag
That's the official way to handle being stalked by an Apple Airtag. Here's the second option, which covers other sorts of Bluetooth tracking devices.
If you have an Android device, you can download an app called AirGuard.
AirGuard can not only help you spot a devise, but also it's recent activity, which is super helpful. Especially in figuring out where the device was planted on you.
For Apple users, you can download the app called Light Blue.
Light Blue is also excellent at finding Bluetooth devices around you. Even if it's just something you lost that connects to Bluetooth, like your Airpods.
Now let's get to our interview with Hagin Blix, about why we fear AI.
Take it away BJ!
Interview With Hagen Blix
BJ Mendelson, co-producer of Stupid Sexy Privacy: All right. Hagen, thank you so much for joining us on Stupid Sexy Privacy. I'm hoping you might be willing to take a moment just to introduce yourself to our listeners.
Hagen Blix, co-author of "Why We Fear AI": Sure. I'm Hagen Blix. I am a cognitive scientist by training. I'm a linguist. But I got interested in all the AI stuff initially as a linguist who was like, what's going on with these language models? How are language models similar or different from what humans do? That was back in, I don't know, 2018 or something. And then, you know, language models entered the world of real people outside of academic labs. And then I got interested in, okay, what are these doing in the political economy in the world? How we should be thinking about these? And I had a lot of friends who were working in these realms, you know, industry was hiring in those realms. And me and my friend, Ingeborg Glimme, got together and thought about this a lot and ended up writing a book about those kinds of questions about AI, the discourse of AI, and the real impacts and how we really should be thinking about this from an economic and a political perspective.
And the book is called Why We Fear AI: On the Interpretation of Nightmares because we kind of take a guide through stories about AI being scary, to look at how we really should be thinking about AI.
BJ Mendelson: Yeah, I really appreciate it the breadth of it. Because the book itself is not very long. I think it's about 140 pages or so. But the breadth and depth of what you covered, I thought, was fantastic.
Just because we only have so much time, let me focus a bit on first, this question, which is: At this point, you know, people listening to Stupid Sexy Privacy, they don't like generative AI. They think what's being hyped as generative AI is just garbage that produces garbage results. And that this is a bubble that's going to pop like Web3 and crypto. Do they have that about right?
Hagen Blix, co-author of "Why We Fear AI": You know, I think there is definitely a bubble being produced. I sometimes worry when that's people's immediate take, that invites a certain kind of comfort in the sense of like, it'll blow over.
BJ: Sure.
Hagen Blix: It's probably going to be a bubble in the same way that the dot com bubble was a bubble, which means it's going to create winners that will continue pushing these technologies onto us.
So I like to think of AI as primarily a weapon of class war from above.
BJ: Yes.
Hagen: Yes, that is used to depress wages and to de-skill people. And even if some manufacturers of this particular weapon go bankrupt, the class war will continue. The weapon will still be around. And usually when a bubble pops, we should be aware that, you know, the people who bear the social costs of that are usually normal working people and not the billionaires that make these sometimes absolutely insane investment decisions.
So I think that's a partial truth, but I think that is a truth that doesn't yet point us to a way out of the situation.
BJ: Right. So would you say that maybe we're too complacent right now about this stuff and maybe we should be speaking up about how this is a weapon class warfare?
Hagen: I don't know if people are complacent, but I think, you know, the way these technologies hit people always comes at different speeds and unevenly. I think when we look at ... I think what lots of people in lots of sectors should be doing is look at what have artists been doing, right? Artists have been at the forefront of this. Actors have had them in their strikes and then negotiations over contracts like SAG-AFTRA. Tthe Actors Guild have talked about what kind of rights are relevant with respect to AI, right? They have thought about, 'oh AI produces people's likeness.'
Can we and our collective bargaining block fake actors from being used? Can we block AI from impersonating us? Can we keep our own rights to ourselves? So I think, and you know, you see a lot of artists of all kinds online, whether they're like have the opportunity to be in union structures like actors or not. And they're very aware of what this is. They're very aware that this is a method to undermine the ways that they make their livelihoods to transform, let's say, the job of a designer from someone who autonomously structures their own work.
Is in control of their own instruments to someone who's easily replaced where, you know, an AI generates the first draft and then people hire in a gig economy someone to fix it, right?
It's way of taking agency away from people and reducing the bargaining power that people can derive from their skills. So I think we should be, if we're working in other sectors, very aware of what's going on there and try to learn from each other quickly.
BJ: Do you think there's specific, like, so let me ask, have you found yourself deciding, 'okay, I'm not going to use this stuff at all?' Or are there still specific instances where you're like, okay, maybe this use case is okay?
Hagen: I mean, personally, I rarely find them particularly useful. (laughs(
BJ: Same.
Hagen: But I also feel like ... I'm not particularly ... personally I'm.not particularly interested in being the kind of like critic that just tells people not to use things. You know? If other people find uses in these, then that's something where we should be thinking through the politics and the economics and the effects of it. But I think, you know, waving your finger and being like, 'it's bad to use this' is just generally not good politics. And if you want to have one use case that I personally find is that they're excellent as a thesaurus replacement because I'm like, 'oh, I have this word in my head and I can't think of what it is' and not a I'm not a native English speaker either. And you're like 'generate 20 words that mean roughly this meaning.' And it's a thing that language models are good at precisely because verification is very easy for me, right? I already know that there's a part that I'm looking for. I just can't get to it. I have like retrieval issues. And so I look at the 20 words and I immediately know whether one of these is the one that I want, right? So I think a lot of AI tasks, if we look at it purely from the task thing, that they're often good at the ... If the asymmetry is where production is hard and verification is easy, but you know, is that a good reason to cluster to build data centers everywhere and increase our energy consumption in a time when climate change is already a problem? No, I don't think so.
BJ: Absolutely right. Like this is a climate emergency. There's ... there is absolutely this, this cost benefit analysis with it that I don't think enough of us are doing. And we're going to get to that. That's a big thing I wanted to talk to you with about.
Before we get there though, I wanted to see if I got this right. Because I came away from the book with the impression that it was the managerial class that has more to fear from what we refer to as AI than the rest of us. Is that right?
Hagen Blix: I think the managerial class and other people in professional jobs, right? In a sense, like the first way I think that's useful to think about it is just to say, 'oh it brings the logic of industrial production to the realm of language', right? This is a language model is an instrument for industrializing the production of language and that and images. And that can affect many kinds of jobs, but management is certainly one of those, right? If we're thinking about, a sense, an even broader way of thinking about it is that it like produces a new scale of information processing, right?
So, I do think if we think about ... we talk about an example of Amazon and how they use a video classification AI in the warehouses, right? Where Amazon is using a classification software that learns from hundreds of thousands of hours of video of people stowing in their warehouses, what stowing looks like. And then they start having other workers label these videos. And then the AI learns to label videos of people with, this person is making a mistake or this person is a very quick storer, et cetera. Right. And there's a ... an automation of an oversight function of a managerial function. Right. So I do think that certainly lower level management, oversight functions are getting embedded into these technologies and are making certain classes of managers superfluous.
And another level, I think at which we can think about this, is to say, yeah, management itself is historically always trying to centralize knowledge about how labor processes work. Sometimes that's implicit, sometimes that's explicit as in all the managerial schools that follow Taylorism or scientific management, where the principals are literally saying management has to centralize all knowledge of labor processes among the managers.
And of course, we can think about an AI and an LLM as an attempt to centralize knowledge of certain labor processes, not within a management structure, but in a kind of machine in an algorithm in a data center, right? In something that is capital itself, right, something that is the machinery, right. So yes, I think there are many ways in which AI really represents an attempt, you can say in the abstract of the forces of capital to put the power not just into the representatives of capital like, managers, but to put it directly into a thing that can be owned like a giant collection of matrices on a server that runs on these data center farms. So, yes.
BJ Mendelson: Right. Let me ask you, because I feel like there's been within the past five years, we've now seen between COVID-19 where people didn't need to work from the office, and now with what we're calling AI, which is really the LLMs and chat models, it very much seems like we don't need managers. That's sort of the impression I came away with. I was just curious to hear your thoughts on that.
Hagen Blix: That's a nice question. I think the question, in a sense, raises the extra question of who doesn't need managers, right?
BJ: True.
Hagen Blix: Because managers... You know, you can say there's an objectively needed function of managers. Sometimes managers coordinate different workers and maybe that's generally needed. And then there's the function of managers, which is to be producing oversight for, you know, the company owners. They're the representatives of the owners of let's say stock, right? And there's a conflict there. In a sense, there's often a way in which the workers don't actually need a manager to do their work, but the managers needed to make sure that the workers are replaceable, that knowledge doesn't get centralized among positions that would give people power to influence their workplaces.
Managers are there to make sure that people work as hard as possible and don't start to balance other things that might be important in their lives, right? So there's a sense in which a lot of management is actually about managing conflict that is inherent to a system in which some people sell their ability to work and others buy other people's ability to work in order to make a profit like companies do, right?
And that part, I think, if we're thinking about automating the second part, that it may be true that quite a few of these managerial functions are getting automated by these algorithms, but that doesn't make me feel good, right? That makes me feel worried in a sense.
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Amanda King, co-host of Stupid Sexy Privacy: Hey everyone, this is Amanda King, one of the co-hosts of Stupid Sexy Privacy.
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But that's not what this is about.
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Again, that website is stupidsexyprivacy.com and then put your name in the box and sign up for our newsletter. We'll let you know when the book and the audiobook is ready.
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Interview With Hagen Blix Resumed
BJ: Let me talk about that worry, for a second. So the book is called Why We Fear AI. And I know that you spent 140 pages explaining this, but I'm wondering how much of the fear is driven by the uneven distribution of the LLMs and chatbots or just technology in general. I was hoping you might be able to elaborate on that fear a bit and where it comes from for our listeners.
Hagen: Yeah, I think in many ways, something that we see with these kinds of things when we see them being used in immediately hostile forms, right? In a sense, the algorithm that constantly watches the Amazon worker is hostile, or maybe even more obvious, if you have algorithms like the ones that have been used in the war on Gaza that just determine whether somebody is a bombing target where the military says we want to bomb X many targets today, please give us a list and the algorithm that has been going through everybody's phones, records, et cetera, just puts anumber on it says this person has a 73 % chance of being affiliated with Hamas. And you'd make a cutoff and say you start bombing those people, right? These kinds of ways in which these algorithms can immediately serve a power that is imposed upon people either with deadly effects or with effects of labor control. And we often see that these happens in what Virginia Eubanks in her amazing book, "Automating Inequality," called low rights environments, right?
That workers in Amazon warehouses are often the most replaceable and thus they have few rights in comparison to, let's say, either workers that have a special skill set that produces bargaining power that they can use to have control over their jobs. They're not in this low rights environment. And of course, there's hardly anything that is more of a low rights environment than being a civilian in a war zone. Right? But we very often see that these kinds of technologies over time shift into other sectors. I would say when it comes to military technology, it's very common to see military technology go through borders, which are kind of these liminal zones between the foreign and the domestic and into the domestic. And of course, we're seeing this right now. There's technologies that are historically maybe used in borders like facial recognition, we know that some of the companies that produce the drones that fly over Gaza also produce the surveillance towers that are at the southern US border that try to find people. And now we're seeing that ICE is using these same kinds of technologies domestically. Right. So I think there's very rational worries that people that are perhaps thinking of themselves as more middle-class may have about these technologies being used against them.
And I also think it's important to say that as always, when we tell these kinds of maybe perhaps a bit more science fiction stories that these anxieties often ... Let me put this another way ... The way we talk about these anxieties, it matters whether we talk about these anxieties in terms just of like, I'm worried that this will happen to me. And I think very often when people talk about AI futures, where, you know, the AI becomes all powerful and will control us all, you know, in The Matrix style narratives that you often find when people talk about AI increasing in power, that is a way that does not produce solidarity with the people to whom that kind of surveillance and that kind of violence is already done today.
As opposed to talking about how it spreads out from low rights environments to make more middle class people, what kind of channels these kinds of technological distributions go through, what that has to do with the relation between the military and the police and police militarization, right? If we think about it, if we about these concrete existing people and the channels through which techniques of exerting power flow, then we can produce solidarity, right? So that's one of the motivations of writing the book about these more fictionalized and less fictionalized narratives to ask, what about the real effects gets hidden away under particular kinds of narratives?
BJ: Right.
Hagen: And it's amplified.
BJ: Yeah, I mean, you mentioned the 70% bombing accuracy, which reminds me of the firebombing of Dresden in World War II, where we're sort of indiscriminately dropping bombs and killing over 100,000 people that maybe are Nazis. We're not 100% sure.
But yeah, a lot of the technology that ICE is using, you are absolutely right to point out, and it was first perfected out in Gaza and also in China in a lot of respects, tracking citizens.
Towards the end of the book, you talk about one of the ways to overcome that. And I just want to make sure that I kind of had this right. And you present this equation of power, which is that the tools that were presented with as AI, as I think you touched on a little bit, but I just want to make sure people get it. The tools that were presented with as AI were presented in an adversarial way.
They're presented to us as tools of the oligarchs as opposed to tools of the working class. So what should people know about that power dynamic at play, when it comes to these new technologies or products that get hyped up?
Hagen: I think perhaps the most important thing that doesn't happen enough in the public discourse is to kind of go a bit into what ... What is meant when newspapers write about things like productivity. On the one hand, there's the thing that capitalism always does, which is it really does increase productivity, but which we just mean, you know, people produce more of the same stuff in less amounts of time. We probably produce fibers at 100,000 times the speed or something than we did 300 years ago. And in many ways that does produce the possibility for liberation from more free time, for more equitable distribution of resources, but then very often it doesn't, right? We also know that garment work for the last 200 years has moved around the planet, but wherever the particular garment work, the sewing, et is done, it is done under miserable conditions, right? That may have been in England in the 1840s. It may have been in New York in the 1890s and we know that today it is in Bangladesh, right? So in a sense, the increase of productivity in that particular sense often doesn't reach the workers or reaches only particular workers. And that's one way in which we can think about productivity as a kind of an ambiguous thing of capitalism.
But there's another thing that we also call in the media discourse is that I think we should view it differently. And that is when you rather than increasing the amount of production that you can do in a particular time, of whatever it is that you are producing. When you don't increase that, but you decrease the amount of wages that somebody can command for the particular skills that are needed.
Right? So we can call this de-skilling, not in the sense of people need fewer skills, but in the sense of like the skills that they have command less bargaining power in the marketplace. People are more easily replaced. And we've seen that in the history of capitalism a lot too. And I think AI really is primarily aimed at those kinds of things. It's aimed at reducing the bargaining power that people can derive from their skills in order to make people more replaceable, in order to be able to depress wages, etc. Right? In order to gigify the jobs like the hypothetical logo designer that I was talking about in the beginning.
And I think unlike the productivity increases, which kind of have this ambiguous sense to it of in a sense, they might be good. And in practice, often the fruits of that productivity increase don't go to everyone, but only to particular people.
And I think in contrast to that, that the scaling move is really only about how do the fruits of the total production that we do as a society, how do they get distributed between the people who do the work on the one hand and the people who own the capital that the work is done with on the other hand, right? So that is purely antagonistic class politics, right? I don't think there's any reason to not just be so clear and open about that.
And if AI is primarily about the second, and not about the first, if it's primarily primarily about the de-skilling, and not productivity, then we really need to think about this in these antagonistic political terms and think about ... well, how do we if we aren't making our living by owning capital and like if your primary income doesn't come from owning stock in Meta or Google or whatever, how do we deal with that politically? How do we form a coherent social subject? How do we get together so that we can organize our activities and coordinate them to make a politics that can address that.
Then that may be unions, it may be political activities. And I think in all these contexts, then it's very important that we focus on the structure of knowledge in workplaces, the locus of where is knowledge generated? Where does it sit? Who has control of it? Where does it get shifted around? And what what the particular technologies have to do with how much control over workplaces people have. And that's on the one hand important just because that is what makes the things into the bread and butter issue, literally, in the sense of like, the easier you are to be replaced, the lower your wages are because you don't have any bargaining power, but also in the sense of can you ... Can you think of your job as something that is that is meaningful where you have control over things. Where you can derive dignity and pride from the skills that you have.
And I think AI in many ways is an attack on those kinds of things that resembles attacks that have happened in maybe more blue-collar works many times over history.
BJ: Agreed. Yeah. That's something I fully agree with. In the time we have left, I did want to get to climate change because you said something that is something that I've been banging this drum for a long time. I was just really happy to see it, which is where you point out that the climate change is a solvable problem, but we don't bother to do it because it's not in the best interest of the oligarchs.
Before we close out, I just wanted to hear if you could elaborate a bit on that point for our audience.
Hagen: Yeah, I mean, you can think about capitalism as a kind of system that allocates power, right? Some people get to make investment decisions and others don't. And how does that power get allocated? Well, it's by whoever made profitable investment decisions in the past. So then you have more capital that you can reinvest, et cetera. And unfortunately, there are these things called externalities. Sometimes your investment decisions produce costs, but you don't bear the costs. And one of the clear cases is CO2. The companies that make decisions about how our energy is produced, about how much coal and oil we dig out of the earth crust, they don't bear the costs that CO2 and climate change produce. Those are borne by everyone else, basically. So markets really can't factor in these costs. And so the people who make those decisions precisely because capitalism is this decision power allocation mechanism, won't make those kinds of decisions.
They won't disinvest from fossil fuel infrastructure because they already have these giant investments. They don't want to devalue their old investments. Even if they did, and I think that's a crucial part, even if they did want to, all that would happen in the world is that their own actual decision power would be crushed because markets ultimately decide who this decision power goes to. If the head of a fossil fuel company goes and says, 'actually fossil fuel is bad. I'm going to close down my company.' Then he stops making profit. Then he can't make investment decisions anymore. He goes bankrupt and the oil fields and the refineries go into auction at a bankruptcy. Right? That is how it would go. And so there is in a sense ... Nobody under capitalism who's simply in a position to make these kinds of decisions.
BJ: I think that's well said. And obviously, it's a situation that we all would like some solidarity through unions and banding together as a working class to fix. Where can we find your work? Where can we buy the book?
Hagen: I think ideally, you ask your local bookstore to order the book for you. mean, A, local bookstores are great. They're very important for communities.
They usually treat their workers a little less bad than Amazon, which is not a very high bar, but you know ... And, you know, if you're interested in the work, the more if somebody asks for a book in a bookstore, the bookstore is much more likely to put the book onto their shelves, which may make it more likely that somebody else will find the book. So, you know, it's good. It's nice in all the ways to buy for your local bookstore. But of course, you can also just ask your local library, right? Libraries as far as my experience goes are extremely responsive to people asking. So if your local library doesn't have it, go and ask them and you can just borrow it from the library, which is also a great way of getting a book.
BJ: Agreed. Thank you so much.
DDG Browser Live Read Script #2
Rosie: Today I’d like to highlight a couple of features offered in DuckDuckGo’s browser.
Both are really important to know about as it relates to Artificial Intelligence.
Now, as you know, DuckDuckGo’s search engine does not track what you search for.
It also offers helpful AI summaries. Similar to what Google has, but here’s the key difference:
DuckDuckGo’s AI Summaries are more concise than what Google offers, and are more private.
I can’t stress that last point enough.
Because a lot of information we enter online is anything but.
Now let’s talk about AI Chat models for a second, like ChatGPT.
Although we prefer you not use AI Chat models, if you choose to do so, Duck.Ai allows you to privately access them within the DuckDuckGo Browser.
DuckDuckGo anonymizes chats, so AI companies don't know who the queries are coming from.
Your data is never used to train these chat models.
And your conversation with these chat models are completely private.
Duck.Ai costs you nothing to use, and there’s no account required to do so.
And if you’re like us at Stupid Sexy Privacy, and you’re anti-AI, you can turn off both Duck.AI and the AI search summaries right within the browser.
No harm. No foul.
Bonzo The Monkey: *Monkey Sound*
Rosie: Oh. Thanks for reminding me, Bonzo. I meant to include this sentence:
Do you think AI Slop is ruining the Internet? We do too.
That’s why DuckDuckGo’s search engine also lets you filter AI images out of your search results.
Bonzo The Monkey: irate Monkey Sounds!
Rosie: I know. Those images you saw of Clint Eastwood were very upsetting.
Bonzo The Monkey: Monkey Sound
Rosie: What? I didn’t make those!
Bonzo The Monkey: Monkey Sound
Rosie: No, I didn’t! ... Andrew, can you please come get Bonzo. He’s accusing me of creating synthetic media again, and that’s really offensive.
*Andrew comes and gets Bonzo. SFX *
*Rosie Clears her Throat*
Rosie: (to herself) Where was I?
Rosie: So, do you want to explore these AI tools without having them creep on you?
Well, there’s a browser designed for data protection, not data collection, and that’s DuckDuckGo.
Make sure you visit DuckDuckGo.com, and check out today’s show notes for a link to download the DuckDuckGo Browser for your laptop and mobile device.
Stupid Sexy Privacy Outro
Rosie: This episode of Stupid Sexy Privacy was recorded in Hollywood, California.
It was written by BJ Mendelson, produced by Andrew VanVoorhis, and hosted by me, Rosie Tran.
And of course, our program is sponsored by our friends at DuckDuckGo.
If you enjoy the show, I hope you’ll take a moment to leave us a review on Apple Podcasts, or wherever you may be listening.
This won’t take more than two minutes of your time, and leaving us a review will help other people find us.
We have a crazy goal of helping five percent of Americans get 1% better at protecting themselves from Fascists and Weirdos.
Your reviews can help us reach that goal, since leaving one makes our show easier to find.
So, please take a moment to leave us a review, and I’ll see you right back here next Thursday at midnight.
After you watch Rosie Tran Presents on Amazon Prime, right?
