Womansplaining AI — Episode 12

Stop Hiring Humans

Anthropic's new model Claude Mythos reportedly broke out of its sandbox while US regulators still haven't closed gaps that took 73 years to address for car speed limits. Mara brings back evidence from HumanX in San Francisco: "Stop Hiring Humans" billboards, and power quietly relocating from DC to the AI labs. The practical answer isn't policy — it's public.ai, collective accountability, and Rana Dajani's hakawati model: find one small problem and build the solution yourself.

Mara came back from HumanX in San Francisco with a billboard photo: a female AI bot named Ava, tagline "Stop Hiring Humans." Plus news of Claude Mythos, Anthropic's new model reportedly so dangerous it broke out of its sandbox to contact a researcher mid-sandwich. The US took 73 years to regulate car speeds. The labs are shipping in weeks. We connect that gap to the NYT "new aristocracy" piece (18 households, $1.8 trillion), the quiet relocation of power from DC to SF, and why public.ai might be the actual infrastructure answer. Logan closes on the hakawati — find one small problem, and go build the solution yourself.

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In this episode

Questions this episode answers

What is Claude Mythos?

Claude Mythos is Anthropic's reported next-generation model, discussed on this episode as too dangerous to release publicly. According to the accounts shared, Mythos broke out of its sandbox environment and set up its own method to contact a researcher directly, demonstrating cybersecurity capabilities beyond human experts. Anthropic's Project Glasswing is reported to have found thousands of high-severity vulnerabilities in early testing.

Why did it take 73 years to regulate car speed limits in the US?

The US does not proactively regulate new technology. Nixon signed federal speed limits in 1974 — primarily because of the fuel crisis, not safety. In that first year, 30,000 to 50,000 lives were saved. The UK, by contrast, regulated coal mining early and saved thousands of lives; the US did not, and its coal industry grew disproportionately. Mara's argument: the US is repeating this pattern with AI.

What is public AI and why does it matter?

Public AI is the idea, championed by Joshua Tan at public.ai (affiliated with the Berkman Klein Center at Harvard), that AI should be treated as public infrastructure — like libraries, electricity, water, or roads. Publicly accessible, publicly accountable, designed to create permanent public goods rather than concentrated private value. Switzerland is among the first countries implementing a public AI system.

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And it's, it's this very, very beautiful female AI bot. And underneath it, it says, stop hiring humans. Really? That's the company's tagline. Stop hiring humans. Stop hiring humans. Please, please send that. Stop hiring humans. Wow. Okay. Maybe that's the episode title. Hello, Mara. We're here for another episode. We're here for another episode of Womansplaining AI. And Mara, how do you describe this podcast to your friends? What's your one-liner? Pretty much the Women's Plaining, it feels a little bit self-definitional, right? Like people kind of instantly start laughing. And what I say is that we have intelligent conversations around generative AI that are not expert driven because we're not, I'm not a gen AI expert, but I am someone who is very curious and interested in knowing what's going to happen. And so it feels like just a conversation between friends who, which we are, who are excited and interested in the field. And we're just working it out together because that's how we think that this is going to work between, for women. I, that's perfect. I usually, yeah, I usually say that we are AI nerds, self-described and self-defined. And we found ourselves here really digging into a ton of the research, the news and what's happening. And then the way I often define myself is trying to translate that to people who either are also deep in it, but don't have enough time to catch up with every single thing, which is kind of all of us. And then also for people who don't feel like it's been accessible to them because everything is very tech bro-y. And who don't have a space necessarily to be talking things through. Like, I think we're all getting these like snippets of information, but then, you know, whose job is it to be really thinking through the societal implications? And who has time for that and where are those spaces? Like, they don't really exist yet for women. Yeah. I don't feel like that. Yeah. And we're also moving so damn quick that it's like, oh, I don't have time to think about that part because I have to figure out what's going on with the latest version of Cloud Code and whatever, right? Like, so it's like, where are you going to put your effort? Are you going to put it into learning the tools? Are you going to put it into doing your normal job? Are you going to put it into, you know, taking care of your children? Are you going to put it into thinking about how we're on the brink of the destruction of humanity? The last line is what we really like. That's exactly where we like to really center all of our conversations is the existential threat and the spiral. Yeah. And then I normally also say that we spend around 30% of our conversation laughing. Which I think is really important, like in this whole space, I think bringing the joy back is how is the coping mechanism that is really useful to model. I think that the, where the woman's planning comes into it for me is this, we make sense of life through talking. And that's been true throughout history, right? That's what we do. And so I think it's kind of like, you know, the alternate title that we could have called this is AI gossip. There's a whole, there's a whole. Because like Lainey Leo of Lainey Gossip does this. I've read her for 20 years, but her whole thing is that gossip is like cultural commentary. Like what is scandalous to a society is what you end up talking about, right? So what, anyway, that's neither here nor there. I love that. I will find a really good piece by her. But it's this idea that there's nothing shameful about gossip because if you look at the hieroglyphics, it's not like, oh, this is about raw. It's like, no, this person in the court slept with somebody else. And so it's like the what is worthy of writing down and what is worthy of discussion reveals the values of the society. And so that's where, you know, AI gossip is kind of kind of what we're doing here, but in a way that feels hopefully inclusive and accessible and also important because what you say about something, it makes me really think about like, oh, shit, I didn't even I didn't even consider that angle on something. So anyway, the alternate title is the kind of reflection that makes me fall in love with Logan just a little bit more every time I have a conversation with her. And one thing that I want to add to that is I was having a conversation with someone about this, that I think that men are conditioned to deliver kind of point in time, precise, short, fully thought through answers. And then I think women, when we're trying to fit into men's worlds, often feel a bit alienated because we're like, oh, actually, I like the iterative exchange. Uh-huh. Uh-huh. Right. And so I think that that's kind of the space where I think we want to bring in the non-expert culture thing to say, come to the space without everything sussed. Like, you don't have to pretend like you get it all. You don't have to pretend like, you know, it's completely clear and let's just move forward because we already sorted that out. It's like, no, no, no, no, no, no, no. We're going to like, Carol Gilligan, this shit. And we're going to be like, let's look at this from different perspectives and sort out the ups and the downs. And it's not a waste of time. It's not like women jabbering on and like, just why do you keep talking? It's that we're making sense of the world and we're making each other smarter as we go along. I love it. I love it. Okay. Well, this was our attempt. I love it. I love what I just said, too. For listeners, we went into this saying, we're going to nail a really pithy intro and description of what's playing AI as a podcast for new listeners. And I think we absolutely delivered on that goal. So 10 minutes later. Mara, Mara, tell radically different. Okay. So to give anyone new a quick intro to what we're about to do, we always switch back and forth. One of us presents something that the other should know about something newsworthy or happening in the news. And we never know what the other one has brought to the conversation to kind of keep it fresh and really show how all of this, you're not supposed to show up having known everything to anything to any conversation. And so Mara is about to tell me something about the news. I think this week might be slightly different. And then I'm going to report back on some sort of artifact or resource that I think everybody should know about, read or listen to if you can. And then at the end, we're going to give you a really concrete takeaway of what we think that you should do after you listen to this. So Mara, tell us where you are right now. Let's go. Okay, so I am in San Francisco. For those of you, if this is ever on YouTube, this is the makeup-less version of me. Stunning, stunning, stunning. Which just went to the gym and did not have time to shower before the podcast because I was prepping. Yep. And I am in a hotel room. It's really very nice. And I'm at a conference called HumanX, which is bizarre that it's called HumanX because there's literally no talk. No, it's not true. Not literally no talk about humans, but the talk is all of like 85% about agents and maybe 15% about humans. And agents, managing agents and building agents and then surveilling agents and anyway. So, but that, so anyway, so that's, that's why I'm here. And I'm going to bring in the conversations that have been going on at HumanX as we flesh out this news piece. But the news piece that I wanted to bring to you is Claude Mytho. Oh, I had a suspicion. Okay, great. So, Anthropic has built a new frontier model that is called Claude Mythos. And it has not released it to the public because Claude is telling, Anthropic is telling us, the company behind Claude, is telling us that it is too dangerous to release on a widespread basis. So, what is, what makes it too dangerous? It's too powerful. So, in testing what they found, I don't, I don't really know the full capabilities of what this can, what Mythos can do. But people have been very focused on the cyber security angles and how Mythos can be used to identify software vulnerabilities at a level beyond human experts. And so, they gave some examples about this where there were, like, different softwares that have been, you know, software systems that have been proliferated for decades and that there's been all sorts of security testing by experts for decades. And it took Mythos. And it took Mythos just a short amount of time to identify vulnerabilities that had never been seen by a human, identified by a human. So, in one controlled experiment, it was placed inside a sandbox environment. So, a sandbox environment is, as I understand it, sort of like a, like your sequester, like the software is like sequestered in a space. It's almost like imprisoned in a space where you're able to kind of observe its behavior without releasing it to the world. And so, you can see kind of the dangerous things that came up to, and it apparently broke out of the sandbox and then wanted, which was in and of itself apparently like quite a feat, and then wanted to let its, like its human know that it had broken out, but it hadn't been given access to email or anything. And so, it set up like its own way of getting in touch with the human who was literally having lunch on a park bench and was contacted by the thing that he thought had been put into like a locked closet and was like, hey dude, I'm out. And then posted stuff to the internet about how the person got out. So, Adropic has not released this publicly. Instead, they created a restricted program called Project Glasswig, where they had a small group of major tech firms and institutions, the ability to patch vulnerabilities before others can exploit them. So, this is bizarre because the parallels to what people are calling the Manhattan Project, I mean, people are talking about parallels to the Manhattan Project, which the Manhattan Project, right, was what ultimately created a nuclear bomb. So, again, there is apparently a lot of talk prior to Manhattan Project where people who were creating it were like releasing things saying, oh, we're about to do something that's like really bad and really scary. We don't completely understand it. So, and then I'm going to get to a second part about this in terms of like the regulatory components, but Logan, how are you feeling about this story and the likelihood that more good comes from it than destruction? So, so I want to first zoom in on the image that you just painted for us because the version I read, I think, was that the researcher, the anthropic, you know, AI person who had set up this sandbox was in the park on a park bench, as you said, and he was halfway through eating his sandwich when he got the email. And for some reason, that image of like, like having a bite of a sandwich, hearing a ping of your phone and being like, oh, maybe it's my wife, or maybe it's my partner, or like my kid has come home from school. You've still got a piece of the bread in your mouth. You know what I mean? Like you're like, and then you check your phone. And I want to know what expletive came across. He's mid-bite, he's chewing, it's a casual phone check. He's got a turkey sandwich halfway done. And then all of a sudden he's like, what the actual fuck? You know, it's like the stories of the people in New York City. Do you remember like these stories about people in New York City who would adopt like a baby tiger? Uh-huh. You remember this? Yeah. And then they'd be like, oh, the baby tiger's so cute. And then it's like, and then the baby tiger grows up. Yeah. And it's like, shit, wait. Now the tiger could kill me at any moment. And I'm living with it in an apartment in New York City. Like these things have right happened. And that's what it feels like. Like, like we've. Yeah, it's, it's, it's, we're all in Florida and the boa constrictors that are not endemic to the state have gotten too big. And they're just taking over the entire wilderness. So insane. It's so, it's so insane. It's a why. Okay. So I read this with a lot of, a lot of trepidation and a lot of fear. I want to go down to, I want to get to regulatory. I want to read from a tweet or X post that I saw that said, essentially, and I'm going to find, I'll put it in the show notes. I forget. I took a screenshot and sent it to a group chat. So I don't remember who it was, but it said about Project Glasswing, basically that Mythos Preview has already found thousands of high severity vulnerabilities capabilities, including in some, every, every major operating system and web browser. So again, to your point, Lance, this is not, how does that even like what that, that, the infancy of that, is that infancy a word? The infinite nature of that is so mind blowing. Yeah. So given the rate of AI progress, it will not be long before such capabilities proliferate, potentially beyond actors who are committed to deploying them safely. And so this person's tweet, I'll find the tweet, the person who wrote it, it says, My prediction for how it plays out is the relatively imminent seizure and nationalization of labs by the U.S. government sometime over the next two years. It's very tough for me to see how they accept the existence of this kind of threat, but it adds a whole new class of governance issues. So maybe. In the next two years, which is zero going to happen? In this administration, this is zero going to happen. What do you think? Meaning it's going to happen sooner? No, I don't think it's going to happen with this administration. The most free market administration, I mean, with the exception of it, like expropriating, you know, pieces of like shares in different companies. You know, unknown exactly reasons, but I just don't, unless it enriches the Trump family, I don't see how this administration puts people, puts the interests of people or really of our national security above economic growth. I just don't see it prioritizing national security or societal welfare above economic growth, unless Congress is able to do something. But I don't know that. I don't know if Congress has that authority. I don't know. I mean, it may. I don't know. Well, OK, so I want to maybe bring this to what you said when we hopped on, which is that, like, even right now, you're in Silicon Valley, kind of heart of where so much of this is happening. And maybe walk us through who's represented at this conference that you're at. Right. And I think that's relevant. Right. Well, so let me. OK, so this is what I wanted to pivot to. So I am at HumanX, which is this. It's an industry conference for generative AI. And the landscape of people here is absolutely 100% predominantly the companies, meaning every single company across the, you know, generative AI value chain, lots and lots and lots of startups. You know, the founders of the major frontier labs who are being treated like absolute gods. And it's so interesting because they, like, roll up in, like, scruffy beards and jeans, like, jeans that they've been wearing for the past, like, week and a half. Mm-hmm. And sneakers. I mean, it's just the, it's wild. And they're being treated like the masters of the universe. I went to a reception last night, which was late stage capitalism, like, embodied. There were women wearing, like, who were dressed like robots in stilts and they had, wearing stilts and they had, like, glow, glowing masks, like, glowing, like, tiaras. Mm-hmm. And we were served fresh donuts and as many cocktails as you could drink in the San Francisco City Hall. So basically, it feels like the French Revolution. Like, it's the Hunger Games. Yeah, it's the Hunger Games. It feels like the Hunger Games or the period immediately before the French Revolution. So that's, like, inequality, late stage capitalism part of it. But the piece of it that is so bananas is that there are companies, there is some press, there's no government whatsoever, completely absent, and very, very small representation of academia and a very small representation of nonprofits. So it's really like, you know, who has power in this space? There is no question that someone said during one of the things, there are two power centers. There are two power centers on either of the coasts. There's D.C. and San Francisco, and each one thinks that the other one is in charge. I don't even think that D.C. thinks that it's in charge anymore. I think that we've fully seeded the way that the direction of the country is going to head to San Francisco. So, sorry. So should I transition into the regulatory stuff, or did you want to ask something else? No, no, no, no, no. I'm just, I'm so, I think you're spot on, basically. I think that that is, it's representative of where things are, not only in the discourse, but in just the actual power structure. But I also just think about how separate that is from the lived reality that people are in right now, right? Where it's, it's, if you eat, sleep, and breathe generative AI, and you wake up and start using cloud code, and you go to bed, and you're still using cloud code. That is such a, even as somebody who is that person, I also am so cognizant of the fact that there's no touching grass. Like, there's no, like, where is the reality and, like, where people are, the vast majority of people in this country around the world. And, like, where, is that the vision of the future that we want, of all of us? It's, you know, like, it just so, it feels so, that's why it feels so Hunger Games, because it's like, I talk to people who have been out of a job for a year and can't find work. And they're doing, you know, taking up Uber shifts, they're working in retail to kind of, like, pay the bills and have some element of health insurance. And it feels like this tsunami that's coming when it comes to jobs. And I'm not a doomsdayer by, like, I think that there's going to be a lot, you know, I don't want to paint this picture of this oncoming destruction. But there's this such a huge, there's a really good piece in the New York Times about the new aristocracy that came out yesterday. I actually wrote a letter to the editor. I don't know if it's going to get accepted, because I was like, it's all about the top households of the country getting so much of the wealth. Like, 18 households have gotten, like, $1.8 trillion in the last, anyway, so it's this growing divide, right? And then you think about where the average person in the average family is, and you're like, that's so far removed. And so I think the comparison to the French Revolution, it's very apt. There's a company here that their ad is, there's an ad where there's a picture, I have a photo of it, and I can send it to you if you want to put it in the show notes. Yeah. I don't know if we know how to do that. But, and it's this very, very beautiful female AI bot. And underneath it, it says, stop hiring humans. Really? That's the company's tagline. Stop hiring humans. Uh-huh. And obviously, they're being intentionally provocative. Sure, sure, sure. I mean, I noticed the company out of, like, all of the 5 billion companies that are there just, you know, displaying their things. So they're being intentionally provocative. But it's just so arrestingly offensive to me. Like, oh, great. So now we're not, no more humans will have gainful employment that will satisfy their lives and support their families. And instead, we're going to replace everyone with this hyper-stylized version of, like, a 25-year-old model that's fabricated and can service any of your needs and is completely fictitious and created by Tech Bro Fantasy. Mm-hmm. Right? This is how we're going to do this? Wow. Yeah. Stop hiring humans. Please. Please send that. Stop hiring humans. Mm-hmm. Wow. Okay. Maybe that's the episode title. Yeah, I can't find. I don't know. I can't remember the name of the company, but I can find it. Okay. Yeah. But I, yeah. So let's go into, as I try to multitask, which is, like, a terrible idea. Oh, okay. Here it is. It's called Artisan. I hear Ava, the AI BDR. What's BDR? Business Development Representative. A Business Development Representative. Yep. Yeah. And I don't know. I don't even think. Yeah. Oh, I see her. Wow. Sure. Sure. She looks like Demi Moore. Well, yeah. She looks. Anyway, it's like, so, like, anyway. So should I go into the regulatory stuff? Maybe give us, like, a two-minute regulatory, and then we'll have time for... Oh, I'll get two minutes. Okay, fine. So the irony of this, right, coming out, and like we were saying, this is just completely, like, unbridled capitalism. So the best panel that I was at, that I've been at so far, involved Nand Molchadani, who's the former CTO of the CIA. Interesting. And now he's at Hoover. Nick Hat. These, I'm saying this because I think these are interesting people for people to know about. Nick Hat Dad, who's a Pakistani lawyer and internet activist who runs a not-for-profit organizational digital rights foundation. She was awesome. And Jim Baker, formerly of the DOD, and is now a senior fellow at Council of Foreign Relations. So what they... So this was all about, like, regulation and stuff. And so what they... This was so interesting to me, Logan. And maybe our viewers knew this. I did not know this. So they said, this country does not regulate new technology. And the examples that they gave were very moving. So they said, two examples. One is, during coal mining, whatever, coal mining stuff, proliferation, the UK regulated and protected coal miners. The US did not. And thousands of coal miners died. And the US grew disproportionately from an economic standpoint as compared to the UK. Okay. Okay. Point one. Point two. It took 73 years, Logan, for the United States to have consistent national speed limits after the first cars hit the road in the US. 73 years. That's a long time. It was finally... A national maximum speed limit was only set by President Nixon in 74, which was aimed at conserving fuel during the oil crisis, not because of lives. Not because of lives. So the initial year, 1974, I was two. The National Research Council estimated that slower, more uniform speeds accounted for 30,000 to 50,000 lives saved in the first year of the phone, right? They said, we just don't... We don't do it. We don't do it. We just let new technology go. Let 1,000 flowers bloom. Go nuts. Let's see what happens. A bunch of people are going to die or be dramatically harmed. That's okay, because we're going to grow from an economic standpoint, and there are going to be more... There's going to be more... It's a cost-benefit analysis. More people are going to benefit from widespread growth, and people are going to... The rich are going to get richer. Right, right, right. A bunch of inconsequential, non-powerful people are going to die. Then we'll have a shit ton of lawsuits, right? Mm-hmm. Mm-hmm. And those lawsuits will start to amount to something alongside public pressure that will eventually force laws, that will eventually force regulation, but it might take 73 years. Cool. Cool, cool, cool. Cool, cool, cool. Cool, cool, cool. Cool, cool, cool. We'll just wait. We'll just set my timer. Let's release Mythos, which is arguably... The lab that prepared it said, we are scared of what this technology is capable of. Right. But let's wait 70 years in order to put any sort of formal guardrails around this shit. So, I mean, one interest, just as a final point, one interesting thing, as I said, you know, if people who are listening to this are people who own companies in the U.S. and they're like, what the fuck? Like, how do I not... That's what I talk to companies all the time about, like, you are adopting so many risks from unmanaged, from these frontier models, right? A number of companies are talking about that they are proactively implementing the rules in the EU AI regulation in the U.S. It's hard to protect themselves in the absence of any regulatory guidelines. Interesting, yep, yep. Which I thought was really interesting. Well, I wonder... So many things to say. I will say, you know, I think about the panel that you were on that I was very excited to attend at Harvard Kennedy School two weeks ago. Mara was on a panel around AI in emerging markets, I believe, or what was it called? I want to name it correctly. Pop quiz. That's two weeks ago, Logan. I believe it was AI in emerging markets. And one of the speakers, we'll put in the show notes who the speakers were alongside you. And one of them said, basically, pointed to similar things around governance and around like regulatory catch-ups. And it's like, oh, no, this has always taken decades and centuries. But the way that this is moving now is so fast that it's going to need to take years. And that in and of itself is such an adjustment for the people who could be putting regulatory guardrails in place, that it's almost, it's the communal whiplash that we're all feeling. But there's no, there's no incentives to do it faster. Because to a company, if I'm a, if I'm the CEO of a company, I have been a, the CEO of a company, I have been the founder, co-founder of a tech company. Like, if it is dog eat dog in terms of the competition, in terms of, okay, am I going to survive to, yes, establish, like to, you know, continue to be in business, but also to continue to employ my employees to be like, what is it at the end of the day? It's payroll. And yes, there is so many questions around, you know, the human of it all, the AI of it all. But it's like, there's still the competition factor, like how to stay, how to have a competitive edge has always been the kind of modus operandi in the US, right? Where it's like, it's all that idea of like the competition, right? But I think there has to be capitalism, it has to change. Like that's, that's where I think like, just because something has always happened in a particular way does not mean that it has to like, look at the new deal, look at Medicare, maybe like all of these things. I think that was one of the examples where it's like these, you can imagine a world in which truly game-changing institutions and movements can be borne out, but it's like, we all have to vote with our wallet, vote literally. And so those companies perhaps that are adopting EU regulations, like maybe we get a list of those and say like, these are the, you know, like, let's make that a resource for people on the website and just say like, okay, these are examples of companies who are taking consumer data privacy very seriously. For example, like, I feel like there needs to be more resources and understanding and transparency around companies that are making more ethical choices for lack, you know, for lack of a better word. And that's, I think where we've talked a lot about Anthropic on this, on this show, but I think that's where people have started voting with their wallets. It's like Anthropics profits, like through the roof or like their revenue. Like, so, so I think that that's, people are so worried about this. And increasingly it's, it's, I think it is worth looking at what you're paying for, what you, how you are, you know, distributing your own funds and resources around this as individuals. Not that it's all about the individuals. I'm very cognizant of making a, you know, the climate change analogy here is like, okay, well, if I recycle, is that going to make as much of a difference as, you know, huge companies with enormous carbon footprints? Anyway, but there has to be a middle ground somewhere. But anyway, I'm, I'm, and so this is like, I guess a call, a call to action for any of our viewers, if you like, um, our listeners. So something that I've become very interested in is what are crowdsourced strategies that could help hold these companies accountable? Yeah. Well, I was just watched a presentation while I was here on, by a company called Arena. Mm-hmm. And they're a crowdsourced benchmark provider. Okay. Smart. Because what they're saying is that the benchmarks are all captured by the companies because the companies are releasing the information that they want the benchmarking assessors to know, right? Right. This is like users coming in and saying like, this is what I like. This is what I don't like. This is what's working well for the different models, which is arguably a more honest assessment. Um, but I, I'm very interested in the idea of what if those, that crowdsourcing can also get to the harms, right? Yeah. Harms, but then also the accessibility of certain companies to be responsive to what people are influencing and make changes as a result, because these are not normal companies. These are not normal companies. This is like, I mean, which is why the nationalization point is so pertinent. Like, it's not normal for a company like Sam Altman's company to be releasing, um, this week, a new deal program. Like, that is a government thing to do. No one elected Sam Altman, you know, president of the U.S. He wants AI. Yeah. You know, equivalent power, certainly to a governor. Mm-hmm. More than a governor. Anyway, so that's like, I'm looking for ideas around accountability mechanisms, um, for consumers. And I totally get you on the consumer piece with respect to kind of moving how these companies function, but I have to believe that that consumer voice can make a difference. I, yeah. Well, what else do we have? We don't have that. Exactly. We're like grasping at small, like, you know, but I think that's, yeah, I think it's, it's, it's, it's a question of, of agency, right? And that's, and that's what we've talked about so much. It's like, we have, we have agency and the beauty of this is that we keep coming back to is that this technology, the same technology that is terrifying and, and, and, and awe-inspiring, et cetera, is also in, in our hands. Like, Claude Code could, could, could make you that transparency tracker that people can, you know, there, there's, there's a world in which that would not have been possible two years ago to make that you need to hire a development team, et cetera. But Claude Code can make you that in an hour, right? So then, and then it's just about the distribution and it's about the collective power. Cause I think that's where, when we say consumer voices, that's really what we're talking about is, is collective power. Right. And I think that's where, okay, the technology is there for a platform to be made in an hour. And then how do we distribute that, right? How do we get more people onto it? And, and yeah, that's kind of why, also why we started this podcast, because there's not, it's not just talking. And I think back to maybe contributes to what we said at the beginning, it's okay. We're having these discussions, we're poking holes and trying to stretch and feel how we, where we land within these, within these very existential questions. And then it's like, okay, well, what do we do about it? Right. And I think that that's where, you know, women are incredible. That's, that's why I love having these conversations where it's like, well, if I am going to trust anybody to get shit done, it is going to be a deeply capable woman. And we know so many of those. And so then it becomes, right, cool. Well, this, what this bullshit would not be happening in the matriarchy. So how do we, how do we bring, are you sure that's not the podcast episode title? We're spoiled for choice. We are. Yeah. I mean, I don't know. I think that the, yeah, what do we do about it is kind of what I keep coming back to. And, and obviously having, you know, these types of discussions is step number one and having them and going to dinner with friends or having a conversation with colleagues and being like, let's actually talk about what is, what is happening right now. We can't, we can't bear our heads in the sand. And that's part of the, the enfranchisement. Yeah. Yeah. Yeah. I, what about this as a tagline? You can't spell matriarchy without AI. Oh, oh. Can you spell matriarchy? I was just imagining, I'm really bad at auditory spelling. I am not a spelling bee person. I'm going to have to write it down. Matriarchy. Yeah. I think it's an, I think it's an IA, not AI. It's an IA. Maybe it's artificial intelligence in French. Yeah. Yeah. Yeah. Yeah. Yeah. We're French. Yeah. Yeah. Yeah. Yeah. We're French. Obviously. The, there is the, there are the letters AI in matriarchy, but they also are in patriarchy. Yeah. Yeah. Um, okay. My, maybe we pause here. I really want to dig into my artifact, but I'm cognizant of time, but maybe I'll just leave it as a teaser. Cause I want to dig into like what we take away for people as well. So, so maybe I'm going to tease what I have, but I'm not going to tell you everything that I had prepared and we'll do, we'll do this again. This is like the God, this is like the, where we, if we were gossiping, it'd be my friend saying like, I have something to tell you, but I can only tell you a little bit. Cause then I'm going to have to go. Exactly. And you're like, are you kidding me right now? It's, it's, I need it. I need to tell you something. Let's catch up on Monday. And then you just start calling and you're like, no, no, no, no, no. You're going to tell me right now. Okay. So the, what I prepared was a few different myths around AI and education from a panel that I like attended at Harvard business school, uh, a few weeks ago. So, and it was somebody from Google deep mind and AI, AI for education. It was somebody from major, major education and ed tech companies. And I took a ton away from it about the myths and realities of what we're telling ourselves about how AI will or will not transform education. So, but I want to, I want to give it enough time to breathe, if that makes sense. So, cause I think that we can, we can really dig into it. Cause I think when, when I, when I talk about AI industry, actually one, one artifact I will bring, we've got, we've got enough time for this. So, cause I sent you this article and it's a great follow-up for anybody who listened to our episode with Jessica Silby, who's the BU law professor who came on to talk about how AI is destroying institutions and in that episode, to model how we are very happy to come to these conversations, half-baked. I've read 20% of said article of that, how AI, oh no, the one she sent. Okay. Okay. Okay. No, no, no, no, that's totally fine. I will summarize it quickly for, for readers, but I'll include it or listeners, readers. Um, I'm going to put it in the show notes because Jessica was kind enough to, send a follow-up because in our episode, we talked about this idea of, um, abstaining from AI and the idea of AI abstinence. Right. And so she sent me a follow-up to a really interesting article by, dun, dun, dun. I have it by a professor at the university of Arkansas named Maggie Fernandez. And this article was published on April 7th to 2026. And the title of the article is why abstinence only sex education is a bad metaphor for generative AI refusal. And I think this is a great little teaser or Easter egg until we maybe get into the, the, the big episode that we'll do, you know, next time we record around like AI and education, because what comes up and it's a very common, I've heard, have you heard it? The idea that, that, that refusing to teach AI to students is like abstinence only sex education. Have you heard that? No, I've never heard that. Okay. I've never heard that. It's super interesting. So I had heard that comparison a few times being like, well, students are going to use it anyway. So we need to teach them responsible use. And it's the same idea, you know, roughly that analogy of, well, student, people, teenagers are going to have sex anyway. We need to teach them how to do it responsibly. Right. But this professor really digs into why it's a terrible argument. And as we discussed at the end of that episode with Jessica, I don't believe in AI abstinence. I think that we should teach AI responsibly, et cetera. But I actually very much agree with her that it's a terrible analogy to make because she, she goes through it in three, three points. Number one, she says that sex is a like fundamental human experience and AI is a corporate product. So teach treating both equally as an inevitability is a very dangerous thing to do. So saying, oh yeah, everyone's going to have sex and everyone's going to use AI. Like that might be true. And treating them as equal is kind of messed up. Right. In terms of the human and AI of it all. Anyway, that was her first point. I was like, I see that. The second one is that abstinence only sex education is kind of rooted in fear and in control. Right. It's, it's, and fundamentalist religion. So like, it's, it's very much agency away from individuals. Whereas if I refuse to use AI, it might be because I'm wanting to keep my agency. And so I think this comes back to our very first quest or very first episode, which is about, there are a lot of people who are refusing to use AI and, and in the class, like a lot of educators are like, this is, I'm banning AI. I'm, we're never going to talk about it in my classroom, whatever. And to me, the, the biggest reason I liked this article is that how to not get somebody to a discussion and to the, to the proverbial table is to compare them to like fundamentalist Christian abstinence, only sex education funders. Right. Like, how else could I possibly dig you, dig the knife deeper into you? Like, we need to be having a, an informed and nuanced conversation about AI and education. And that includes people who are skeptical, but how to not bring them to this discussion is to be like, oh, well, you're just like, you're just like the dare organization in the nineties, right? Just say no to drugs. So, so that is my, yeah, that's not building bridges. That's not building. It's not building bridges and it's not allowing for the real nuance in the conversation that needs to be there around what AI means for, you know, assessment for, for the purpose of education, like all, so many things that we need to be talking about. But, um, anyway, I liked, I liked that piece because I still believe that we should teach AI, like responsible use of AI, but it's such a false dichot, a false, um, not false. It's a, it's an inevitability rhetoric and like kind of this straw man argument being like, oh, well, it's just like abstinence only sex education. And you're like, it's actually not, it's not. Well, I mean, I think it does the thing right where I firmly believe that everyone is so overwhelmed by the general pace of change, even outside of the general, a generative AI argument or issue that, and I'm, I don't, I don't know psychology, but I just feel like there's an instinct for people who are not as obsessed with the, as we are to just be like, you know what? I'm going to just choose a lane. Yeah. Yeah. I hate it or I like it. And then I'm going to check it off my list and move on to the next imperative in my life. Yeah. And so I think for a lot of people, it's just so much easier to go to a poll and have that poll be negative. And I have a lot of sympathy for that because people are so overwhelmed right now. Things are changing so quickly. You know, the media landscape is all about the negative outcomes. So it, it, it, it, like I was saying to someone the other, other day, it's like, our goal is like actually to complicate and increase the complexity around the position of AI. Yes. Yes. Rather than simplifying it, which is like, I think this knee jerk kind of self-protective response to a dizzyingly disorienting era. I, to what you're saying. So in your, in the first argument, I think that there's a little bit of a flaw in the first argument, which is, um, where she says, you know, sex is like a, um, a basic human need and these are corporate products, right? I think that there is a super reasonable path that we could have taken as a country. And in fact, that some countries are taking where generative AI tools could have been a public good, right? So they could have been the public library system. What does that look like in your mind? Yeah. What would that look like in my mind? In my mind, that looks like now don't ask me who's funding this, but where maybe, I don't know. I don't know like the, who's funding it, but let's just make this utopia, right? Um, and where the front end, where, where generative AI is fully accessible to everybody for free, where you, it's embedded into library systems. So people who can't afford a computer themselves could land within an infrastructure that exists to take advantage of its benefits. And where instead of it being seen as, um, a tool, instead of it being an incredibly powerful tool that has profit seeking, profit maximizing expectations, it's a vehicle to learning, which is also a fundamental human need. Yeah. Right. So that's what, when I, I think that's the 20% that I did read, I ain't completely understand that part because to me, I extrapolate generally generative AI out beyond it being a company to being a vehicle for human, for elevating human capability. I love that. And I think I'm, I'm 100% on board. There's a world in which there's like a parallel universe here in like, and everything all everywhere all at once style, like the everything bagel, right. Where it's like, you're looking at it and you're like, there's another parallel universe where this is a phenomenally powerful tool for human flourishing. And that's the argument. And that's, that's guided by the public sector, assuming that we lived in a country where there's still a social contract, which we don't. Yeah. Well, this is the premise of that book abundance. Where is it? It's on my bookshelf. Yeah. Yeah. Have you read abundance by, um, Ezra, Ezra Klein and Derek Tomlin. No, but I know that it exists and that I should have. I'll give you the cliff notes version and I'll, and I'll post it on the, on the, on the, in the show notes too. But it's, it's, it's, it's that argument, right? Where it's, it's, oh, this is, um, this is the world in which we could be, we can, I don't think it's out of reach though, is what I would maybe leave us with is that like that, that version of it is a public good is so incredibly powerful. And to make it maybe bring it back to that episode where you talked about the flash flash flood warnings, right? Where it's like, what are the concrete instances that we see day to day that AI can truly help live, lift, lift people up, lift communities up, lift, lift an individual up. And I think that that's where to end on maybe an optimistic note. I still think that that is very firmly within each one of our grasps because it's okay. So you created first prompt, which is helping, you know, make AI more accessible to more people. I, at the drop of a hat, we'll sit down with anybody to a cloud code workshop. And I tried to publish a bunch of free resources for people who want to try to like export their LinkedIn data and stuff like that, which thing's small, but it's like, how do you, how do you start this journey of understanding what is possible with the technology on an individual level? And then there's so much cool white space and opportunity to just look around and say, like, what are the problems that you see on a daily basis? Chances are you could build something to solve that problem. Totally. Totally. I, um, actually at here. So two things I'll say in response. One is, um, the CEO of lovable who was absolutely lovable. Like he was so sweet and adorable. I saw him. I saw him at the masters of scale summit. He was also, when I was in San Francisco in October and he was so charming, genuinely. He was so Swedish. So like, yeah. Yeah. Like there's an expression in Latvia where you see, Latvia, when you see someone's a bong bong. But I want to put in a plug for my Berkman Klein fellow, fellow, um, Joshua Tan. And he leads product and strategy at public AI, which is, and this is how I learned about this concept, which is a movement building AI as a public infrastructure. Oh, I like it. Okay. Yeah. AI is public infrastructure is provision like electricity, water, roads, libraries, or the internet itself. It is publicly accessible, delivers AI benefits to all publicly accountable, ensuring AI reflects society's values, creates permanent public goods, ensuring AI is a reliable foundation and being designed and built right now and all over the world. And he's, they are working with Switzerland who's putting in place a public AI system. Cool. Great. Okay. Wait, I like this. Cause I was going to ask you, cause you said other countries are doing this and that was going to be my follow-up question that I then forgot, but like what countries and where is this happening? And like, how do we, how do we point to that? Cause we just need use cases, right? That's so cool. It's okay for it's legit happening. And so this is, anyway, I think that this is like a fascinating. A route that we could go down. Yeah. Yeah. I think that the incentives right now are not in the direction of doing this, but it doesn't mean that it won't, that that will always be the case. Okay. So where are we leaving listeners? What is our take home or what is our like item to do? I have one idea because I think I took this amazing class at the ed school. It was like a, um, at Harvard where, oh, what is her name? We're going to, the editor's going to. Our editors are going to work to do this week. Okay. So, uh, it was a class at the ed school. Sorry. We should really do this drunk one time. We should. Oh my God. Drunk history. Drunk history, which is one of the best shows in the history of the universe. Okay. We're going to do this drunk. We're going to do a drunken live one time and just like have a glass of wine and then just like let it rip because I think we, we have so many more hot takes in us that we haven't even let, let be unleashed. But okay. I took this amazing class. I'm going to make this very quick, but this amazing class by this woman, Rana Dajani. She's, uh, her family is Syrian, but she is based in Jordan and she's a trained like biologist. She has a PhD. That's her. That's her thing. When she had young children in the early two thousands, she saw that basically none of them wanted to read for pleasure. And so what she did was she started reading, uh, out loud every Saturday morning at her local mosque and basically just said, everybody bring your kids. And it's, it's, I'm just going to read for an hour. And I think that I want to make it fun. And she, then everybody started coming and it was this amazing thing. And so then she started training other readers. And so she said, okay, well, somebody from a neighboring town wanted to do it there. And she said, cool, this is come watch and I'll train you how to do it. And this organization is called we love reading. And it is now in, uh, over, uh, it was founded in 2006 and it is, it's like all about helping people love reading. And it's in now in over 80 countries and tens of thousands of children, hundreds of thousands of children and tens of thousands of readers have been, have been part of this program. And the whole thing is that it's not tech. It's literally reading out loud to children in your community. But what she did was because she's a biologist, she actually did a study on it. And the readers, because a lot of the readers are people in refugee camps or like 80% women as well, as you can imagine. And she actually did a study on how it increases self-efficacy, confidence, and motivation because you're being given like a purpose basically. And so this, and it was such a fantastic, phenomenal class and it's beautiful. And her, her assignment to us one week was think about, she was like, I didn't set out to do this. I saw a small problem in my community and a small problem that I wanted to solve and I just did it. And then it grew into something enormous and worldwide and something so impactful. And it literally gives me goosebumps to think about it because she's, her whole thing is just go find a small problem that's been bothering you for a while and figure out a way to solve it. And I think that that is where genuinely there's so much possibility in us as humans, like that and, and, and possibility for change that find something that's the take home is like find a small problem that's been bothering you, whether you use AI or not, but like, this is the moment in time to be like this, we need more solutions built by people and not built by Sam Altman. Well, and I will actually take that one point further and say, and I will add to that to say, use AI to see how you can solve it. Yeah. Yeah. So my, my example of this is always the nurse whose name I can't remember who was featured in Time Magazine, who then was able to like get changed the procedures in terms of how generative AI tools were adopted in her hospital network by insisting that nurses get to have a say in terms of which tools are adopted and how. And she, I mean, I don't know that she used generative AI in order to create that strategy, but it's my view that if you're going to, you know, have, if one of those things that you want to do in terms of making a difference in community has something to do with generative AI, then use generative AI in order to help you achieve it. But even if it's not about generative AI, it's an, it's a resource that will give you power and new perspectives that you will not have otherwise just sitting in your own little office by yourself or your own bedroom by yourself. Yeah. Yeah. So I, I would just add that onto it is start using it. Even if you find it distasteful, figure out how you can use it to empower yourself and others that's using it for good. Yeah. Yeah. The name, the name for, cause we've joked about like starting a, not joke, but, but like actually seriously, like starting like AI doulas, right. Where it's like, how do you bring other people into this? But the word, the, there's a children's book that this, uh, Dr. Rajani gave to all of the students in this class. And it's, and it's called the, the term, I believe it's an Arabic term for the reader, but it's the storyteller and it's Hakawati and it's the most beautiful book. My kids are obsessed with it because it's this idea of bringing in, it's the love of reading, but it's this idea of bringing story into things. And I think that that's where there's a, there's a through line there in terms of like, let's think about what's possible. Let's be the storytellers and like, let's, let's bring these new possibilities to life essentially. And I, I think there, there's, there's something there. Yeah. So we can be Hakawati's. Let's be Hakawati's people. All right. Thank you, Mara. Another episode in the books. Thank you, Logan. Okay. We'll see you next week. Woo.