B (3:23)

After the end of World War II, nuclear weapons made large scale interstate conflict prohibitively expensive. Expensive. I mean, you basically destroy the world if the big states fought first through the Cold War and then even after. We have some conventional wars, but they're not on a global scale because the fear of nuclear weapons keeps that out of bounds. So most of the wars that we saw Since World War II have been guerrilla wars when the actions of the state mismatch what the desires of the people and they erupt. There was a paper back in the 90s called that focused on fourth generation warfare, what they called the, you know, transition of conventional warfare to what they called fourth generation warfare, which is guerrilla warfare, and described how it was becoming the predominant type of warfare in the world. So I picked up on that and started focusing on how that, how guerrilla warfare was changing. And then when the Iraq war kicked off, I got a good example of how wars were being changed by the networks that were exposed to. And networking has changed the way guerrilla warfare works. And that led to the book. And a lot of my writing says that.

A (4:48)

How is guerrilla warfare similar to something that my audience will be flying, familiar with and passionate about? How is guerrilla warfare like open source software?

B (4:56)

Okay, well, that was, that was the insight I made back in 2003 when I started writing about it, is that you saw the conventional analysis coming out of what was going on in Iraq, coming out through the papers and through papers being written inside of the DoD from firsthand accounts that I was hearing, it didn't match what was going on in the ground. So typically when a guerrilla movement takes on a state, they mirror the state, meaning they have a military wing, a political wing. They have certain functions that act as a kind of a state, a shadow state that challenges the existing state for dominance. And that the guerrilla movement protects itself by decentralizing, meaning that, you know, you go, if you flip one person lower on the totem pole, you get to the next level and, and then you go to the next level, next level, next level. And eventually you get up to the command cell and you take them all out and the gorilla movement falls apart. What we saw in Iraq was, was completely different, is that instead of one group, there were 70 different groups. And they had all different motivations for taking on the United States, taking on the Iraqi government. There are a bunch of different flavors of jihadi. There are pro Saddam nationalists, anti Saddam nationalists. They were criminal groups, there were tribal groups, each trying to carve out some level of power out of the state. And if they were all just coordinated, that they wouldn't have any kind of impact, but they tended to coordinate. And what I saw is that there was a method to the madness. I wrote a New York Times op ed in 2007 describing what was going on. That mirrored my book, is that these groups coordinated their actions through the network in a, in a decentralized way. One of the first things that went up in Iraq right after the invasion was the cell phone networks. It was flat. The cell phone towers went up. Everybody had a cell phone. It allowed that kind of coordination, plus what was going on on the Internet. These groups communicated through a process I called a stigmargy. You know, and, you know, the way insects communicate is that they don't like, talk to each other, obviously, is that, say an ant finds a food source on its way back to the mound or the nest. It lays a chemical trail pointing out that there's a food source to be accessed. And every ant that follows that trail and still finds food, it reinforces that chemical trail goes on and on and on until the chemical trail is like a bright superhighway where all the ants are going to down it to get to the food. And then eventually ants that get there and there's no food, they come back, but they don't leave any additional reinforcement and the, the chemical trail evaporates. What was going on here is that they were communicating through reports of what was successful. So if it was reported that this kind of attack against this kind of target was successful, everyone would copy it. And that was an indicator to me that the thing, what was going on was using an open source model, something I picked up when I was an analyst in the tech field. And the open source model uses a decentralized kind of approach to software development, where there's a common plausible promise to what the software could become and that every participant sees that possible promise in a, in a different way. You know, they, they, they see it meeting some need that they have that may not be shared with everybody else. And they all work to improve things. And, and if there's an improvement that's offered to the software, everybody copies it. And there's a philosophy they use, is that you throw something against the wall, some innovation against the wall, and if it sticks, you've made some progress. They're not fearful of failure. So there's a lot of tinkering at the grassroots level where everybody's pitching in. There's no barriers to entry in the open source model, meaning that anybody could participate. You don't have to go through any kind of hiring process or vetting process. You just jump in. Every innovation you make advances the overall group's goals. So in the case of Iraq and their, and their guerrilla war is that the plausible promise was to get the United States out of Iraq. And every group signed on to that. They all approached it in a different way that united them despite the diversity of motives. Because if you took any two groups out of that insurgency, put them in the same room together, they probably kill each other. Whether it's doctrinal or just bad blood, tribal differences, whatever it is that they would, they would not get to get along. The plausible promise that unites groups in an open source insurgency or an open source protest is usually really, really simple. It's a very simple, you know, idea. It's not complex. It's not, doesn't have a lot of nuance. It's just if you take a case, if it goes to a protest, a protest would be like, Mubarak has to leave, they have to leave office, and that's it. And all of these different groups, all of these different individuals who have different reasons for joining, would join the protest. Do you follow me?

A (10:55)

That I am following you? Yes.

B (10:58)

So the open source model is a lot of nuance and a lot of depth, and it worked very, very well from, you know, in terms of describing how this insurgency worked. Yeah, I mean, so one of the limitations I found in this model though, is that it would never be able to build an army of sufficient size to take on the state's army and wipe it out. The groups wouldn't come together that way, and they're too small to undertake massive attacks. But there's a workaround for it. And the workaround was that in modern societies, societies since World War II would become increasingly dependent on systems and Systems are everywhere. I mean, we could see it in our own society. If we don't get electricity for five minutes, everything kind of tends to break down. But we have, you know, systems upon systems that are connected to systems, and they all have to be working in real time. And we're completely dependent on them now to a degree that somebody 50, 60, 70 years ago couldn't even imagine. The same was true even in early Iraq. But what that enabled and what that enables is something called a systems disruption, is that these groups can attack points in these networks. This is these infrastructure networks or social networks, and disrupt them in ways that cause cascades of failure to go through the entire network. And it's an evergreen attack. If they were blowing somebody up or killing them, like at a terrorist attack, a terrorist attack has diminishing returns on the fear and disruption that it creates. Whereas if you're disrupting a system, it has lasting effect. It's always going to have a meaningful impact. The kind of dependencies and the interconnections that we and the tight coupling of these systems that these networks that we have today allows these groups to undertake attacks that give them amazingly good returns on investment. In some cases I've seen, for every dollar invested, they get a million dollars of damage in return. And so we're seeing like a little version of that when we were looking at drones versus modern aircraft and missiles coming from the West. So you have this relatively inexpensive system at $100,000 being destroyed by a missile that would cost 3 million bucks. So that's a pretty good rate of return. But if you are disrupting an electrical system or you're disrupting a fuel or, you know, pipeline system for, for an oil field, you know, you can, you can generate massive returns on, on a relatively small attack. And given the size of these, the number of different nodes that you could attack in a. And it. And the systems that networks that we rely upon, it's relatively easy to do, meaning that it's kind of hard to. It's impossible for us, for the state to defend everything. It means that there's always going to be opportunity and there's a good chance you'll survive it. Whereas a terrorist attack, you probably won't survive the attack. In the case of systems disruption, there's a high likelihood that you'll survive.

A (14:14)

So we have this kind of asymmetric situation where somebody with a lot less money is able to destroy, in this case, something that is much more valuable. Sticking with drones for a moment, what is the response then? So, okay, we have Drones being used in the Russia, Ukraine war. And the drones are highly successful, especially asymmetrically. What is the response typically historically, however you see it from the more powerful force that is getting punished in this asymmetric way. How did they adapt and how, and how does that eventually play out?

B (14:45)

Well, it is possible to outlast them. In my 2007 op ed I, I suggested to the folks at the dod, I, I know the chairman of the Joint Chiefs read my book and he was using it as a guide. They should try to divide the insurgency. Now typically the way you get rid of a protest movement or insurgency is you try to negotiate with it. If it's a, if it's a one that you can't defeat easily militarily is you negotiate with it and conduct some reforms and it melts away. With an open source insurgency, since there's dozens, thousands of different groups involved and individuals that are meaningful to the insurgency, you could never come up or craft a reform program or a negotiation platform that works. What you could do and what they did in the Iraq war was exploitation, a failure. The failure was that portion of the insurgency, the Al Qaeda in Iraq decided to widen the war and attack the Golden Mosque that was revered by the Shiites. That led to big Shia militias cleansing in Baghdad neighborhood by neighborhood, big formations that the US wasn't attacking and the Iraqi government wasn't attacking. Participants in the Sunni insurgency weren't able to mask the forces necessary to defend themselves against these, these militias. And they were losing again and again, neighborhood by neighborhood. It once they came together, they were attacked by US forces. The exploit was to start offering protection to the, the Sunni groups because they were in life and death. They were about to wink out. So, so they offered him protection and this was the kind of the tribal kind of deal that was cut that allowed the US to split the open source insurgency in Iraq and cleave away enough groups that the remainder wasn't sufficient to continue the so exploit mistakes. It's possible that the open source insurgency will fork. And that's what happened in Iraq. It's not easy once it gets going because once an open source insurgency app, you know, gets up to a certain level inside a country, it starts to create its own weather. And what I mean by that is that once there's a sufficient level of disruption in the country, electricity, water, fuel, you know, outside income from the pipelines or whatever they're exporting, ports are disrupted. What happens is that a lot of groups form to continue it because they profit from that disruption, offering Alternative source of electricity, alternative sources of gasoline, et cetera, et cetera. And it's really hard to kind of break out of that. It's far easier if you catch it really early on.

A (17:33)

You talk about this concept of the network, which is social media, mass movements. People are very easily influenced by their phones that they're carrying with them. Everybody has the ability to see the same thing, whether that's true or false or outrageous or whatever. And this movement can kind of occur if we bring this to the Russia, Ukraine war. You had, as soon as Russia invaded a lot of Western companies, hey, you know, McDonald's is leaving Russia and Steam the, the, the computer game software. They said, hey, we're not going to serve Russians. The Swift system shut down Russians, Airbnb, there was this whole movement to basically de person Russian people. Maybe one example of the network here, and I want to bring this into something that is maybe we use the term open source a little bit metaphorically, but very popular open source project, Linux. Last year, several Linux maintainers in Russia were kicked off of the project because of US sanctions. So you have one of the most important open source projects, Linux, and now Russians are basically not welcome to partake in that. And Russia, of course, is talking about forking the Linux kernel and doing all this sorts of things. I just wonder if I could get your analysis however you want to take that on that situation.

B (18:50)

Yeah. Well, the open source network model that I worked on for the Iraq war persisted and it started moving into different areas. We saw it emerge as the mechanism for mass protests and that Arab Spring, and there was all those protests that toppled governments across North Africa. And then we saw it in Colombia with Nomas farc. We saw it in Puerto Rico when they got rid of the governor. And then it started to morph into politics, meaning that it started to be used as a way to get politicians elected. And we saw that happen in 2016. Basically an open source insurgency put Trump in the White House, was opposed by all the press, most of the institutions, but it operated outside of that and was extremely innovative and possible to kind of break or slow down or dissuade and to put Trump into the White House. That network model has started to become part of our daily lives. Now, the other part is that what I found is that networking, social networking in particular, creates a massive change in how we think. We've had the last big one that we had in terms of changing at a fundamental level how people think and how their neural connections, their neurons interconnect, how their brain is Wired happened with the printing press. It changed people. It fundamentally changed people. It changed how they thought, how they structured their thinking. And that change of the printing press created big changes in society and how society was organized. You know, moving towards bureaucracy, moving towards markets and contracts and corporations, moving towards organized science with papers being written and everything would be structured in terms of what made sense to a mind that read for information. We started to form governments based on a constitution, a written document, that kind of thing. Now we're going through something similar with how social networking is rewiring us and we're reading less. Especially you look at the younger people out there right now, they're reading very little. What people do when they're confronted with social networking, that they don't read everything, they scan it. They scan the feeds and the vast amount of information, the torrential flows of information that are like assaulting them on their, on their smartphone or on their screen. And they scan it looking for items, posts and videos and pictures that capture their attention, that fit into patterns that they're curating for themselves, that they're maintaining. And this kind of pattern matching become kind of a group activity that there are, you know, very common patterns that emerged in the, in the political sphere that millions of people contribute to. They analyze every news event, every new item that appears within the context of that pattern, and they fit it in like a pu puzzle piece into this master puzzle. That pattern is used by tens of millions, hundreds of millions of people to make sense of the world because it's. Otherwise, it's just too much information they can't make sense of for. And so they're using, you know, people adopt these patterns as their own. It changes the way they think and how they approach things. In the US we have a red pattern and a blue pattern. The red is more decentralized than the blue pattern. But people use those as a, as a. These patterns as a way to get through the day. So what happened in Ukraine with the Russian invasion is that there were. There was a big group of people who saw Russia as the, and particularly Putin as the person behind Trump getting elected. They, they framed it as Putin being ultimate evil, kind of mastermind behind the Trump disruption. And when he invaded, there was an immediate reaction, you know, from. And the people who curated that pattern, people who believed in that. You remember all the years of Russian collusions, prosecutions and investigations during the first term of Trump's. Oh, yeah, well, those folks already had that pattern. When Putin invaded, they sprang into action and they created what I called a Swarm. The one thing about an open source insurgency is it can mobilize very, very quickly, is that it has no barriers to entry. Anyone can join. There's a simple, plausible promise that once it's broadcast out to everybody, everybody could see it and then make a decision and they just jump in. They can contribute in any way they see possible. In the case of Russia's invasion of Ukraine, it was immediately framed as kind of return to another Hitler emerging in the European continent. This has to be stopped. As ultimate evil advancing. The swarm started waging war the way it wages war, meaning that everybody contributed to disconnecting Russia. Since it's a network kind of consciousness, it sees disconnection as the ultimate harm, meaning that disconnection means irrelevant, means poverty, means, as it does, remember, when people get canceled, you know, they lose their job, lose their. They. They can't go on any of the forums, they can't even do anything online because they'll. Their accounts will be suspended. It's becoming kind of a non person. So the swarm emerged so quickly, it took about two weeks for it to go from zero to a whole worldwide effort where it's not just the government. So it's way ahead of government policy. The government policy would have been nice and structured and they would have taken measure by measure and trying to. To squeeze Russia into accepting an alternative or dissuading them from going farther. The swarm just went. All these companies and all these agencies inside of these different governments acted independently. They were taking this policy on their own shoulders and moving it forward, making whatever kind of advance they could. And it didn't stop. Disconnection wasn't the only thing. There was all sorts of money and technology and other things that were flowing into Ukraine to help them defend themselves. The swarm thing was scary. Is that for years. I mean, the policy or the kind of conflict between the US And Russia had a certain structure to it because both had incredible nuclear stockpiles. Russia has even more than we do. It was a kind of a protocol and a set of lessons that we learned over the years, over the Cold War and after the Cold War to surviving kind of conflicts between the superpowers or nuclear superpowers. And all that was thrown out the window. And the politicians kind of. They saw this swarm developing and they just jumped in front of it and it started waving the baton like a parade that they had to get ahead of. Follow me. And Biden's rhetoric went right through the roof. And Putin was returned to Hitler. And this is the threat to all of the west and they're going to invade the rest of Europe and all that other stuff. And it escalated right up. The scary part to me was that this swarm at the time, while it was running hot for about four or five months, was something you couldn't even argue against online. If you even said anything against it, you would be just piled on mercilessly. It only framed it because it was like this group consciousness. It only framed kind of a resolution to this conflict as a complete win, like absolute win. There had to be. Russia had to totally capitulate, withdraw, maybe even disarm, get rid of Putin in order to kind of resolve it. There wasn't any middle ground, which is kind of an unrealistic kind of approach to things. If Russia wasn't as big and, and, and was it such a source of, of wealth production through oil and gas, it probably would have folded the country. But to let the kind of war and peace be decided by a network swarm that's mindless and aggressive to the hyper aggressive that you can't argue against. It doesn't see nuance. It doesn't see shades of gray. It doesn't see anything except the absolute destruction of its enemy was pretty disturbing to me. It was like, I'd rather not see it again.

A (27:22)

A slight diversion here. Recent news. I want your, your, I'd love your take on this. We wrote about it in our own newsletter, but I'm quoting here from the news. The Secret Service said it has foiled a telecommunications network of tens of thousands of devices that could have been used to wipe out cell networks in New York City. It was found in a couple apartments. There was basically a hundred thousand SIM cards that were set up there. What was, without going into more detail or assessment, what is your assessment of what happened there?

B (27:51)

It was a criminal network and they were using those telephone nodes as US Numbers that they could then use to call people and spam them and then call it potentially internationally. The whole idea that it could be used as a denial of service attack is pretty overblown. I would even say that's the most useful.

A (28:14)

Yeah.

B (28:14)

Thing for it. The worst in part was that it was a Chinese criminal network. And we know Chinese criminals or tied to China can be nationalized pretty quickly. So if there's a Chinese criminal network operating abroad, they could quickly put pressure on all their family members everywhere. They could be all jailed and their mainland connections if they don't cooperate, and they do. Here's how I would use it. If China ramped up to attack Taiwan, for instance, it was a Kind of a surprise attack, you know, very little notice they started going across us, was formulating a response. This could be an avenue attack that would cause disruption and confusion. So I wrote about this called the Zero Day War attack against the United States. Using drones as the primary means of actually breaking infrastructure in a deniable way across the United States. Hit a bunch of nodes and hit them using basically a container of drones at the major metropolitan areas. You could amplify that by using a network like this to send out police alerts, other kind of forms of misinformation via text or even, you know, voice synthesis. You can even have AI conversations where people are, you know, with higher levels of government and just to cause confusion that would delay the US response. So if you can create enough disruption and confusion in the United States during the critical early phases of that war and focus its efforts on it, on maintaining domestic security and, and order, you could get maybe two weeks, three weeks before things started to wind down. And even though the fingers would be pointing at China because it's relatively non lethal, it wouldn't evoke a kind of a nuclear response or anything meaningful other than kind of similar efforts in China which are harder to do. And then China would have completed its invasion and it would be over. You know, as we saw a container of drones, people don't understand this. I was writing about, you know, using, taking a container of drones and, and driving them inside the United States or either a shipping container or, and, and the people needed to kind of launch them coming over the border when the border was open for four years during the Biden administration. And a lot of people connected to the Chinese military came in through that is that containers could launch upwards of 170 small drones or even moderate range drones that can run multiple attack runs against any kind of target. And if you're focusing on systems disruption and critical infrastructure, you can take out, say you take out every major substation in the United States. And a lot of those substations have equipment that you can't replace for two years because the production is out there. Even if you wanted it, you couldn't get it. Recently, in the last year, long after I wrote about it. What a Zero Day War attack would, would be is that we saw it in Iran and we saw it in Russia would. When a Ukraine drove a container of drones or two containers, one container went up to the Murmansk area, other one went to eastern Russia and they launched drones out of those containers. They rolled back the tops, you know, and attacked Russian air bases. You Know where they based their strategic bombers. And we're talking thousands of miles away from, from Ukraine. And they used people inside Ukraine wireless telephone networks to, to allow them to fly these drones in first person view into their targets. So even the small drones, if they could precisely, they hit their targets, you know, evade defenses and hit their targets with precision. Even a small amount of explosive could do amazing amounts of damage. They'd analyze the planes and the planes were all sitting out there on the tarmac and they attacked them and it was very, very successful. The case of Iran recently, Israel had smuggled in a bunch of drones to various locations in around Tehran and other places and used those drones to attack a lot of the air defense systems that protected the capital and other places and allowing Israeli jets and US jets to attack with relative impunity. So it was really hard for Red to block this because it happened so suddenly. And then this, you know, the safe house that they launched from, they launched from the roof of a safe house, just disappeared. You know, just, you know, people left. There's no one to, no one to arrest. So yeah, that's how I'd use the sim network.

A (33:12)

Are there other specific examples of concrete examples of system attacks that maybe most people don't think about, but you do think about and maybe even makes you sleep poorly at night?

B (33:25)

I don't sleep poorly at night ever, but people read my stuff, tend to sleep early at night. No, I mean, you know, I wrote Attack, I wrote about an attack on gwar, which is the biggest oil field in the world. The kind of granddaddy of all 5 million barrels a day out of Saudi Arabia that pumps every day, the loss of which could have put oil in 2008 up to $300, $400 a barrel. By the way. I was pulled in and I was talking to a bunch of hedge funds back in 2005 or so about the Iraq war and their disruption of the oil infrastructure. I mean, one of the reasons, I think the biggest reason the US invaded Iraq was to free up the oil production in Iraq that was capped by sanctions. And if they could get rid of Saddam quickly, they could remove the sanctions because of his departure or death, gin it up to 5 million barrels a day and put 3 million extra on the market. Just as China was starting, Chinese demand was starting to pinch everything. So what happened is that the open source insurgency began attacking the oil infrastructure so successfully that the production actually fell from well below down to about a million barrels a day, million below its sanctioned level. And they weren't able to Revive it. Also at about the same time, a group called mend, the Movement for the Emancipation of the Niger Delta, was using similar tactics in the swamps of the oil production in Nigeria. They wiped out a million barrels a day. So those two ended up, as predicted by my theory, put pressure on the oil market such that the price of oil went up to $147 a barrel at its peak. And the entire global economy just screeched to a halt. The gears were grinding. It was getting terrible. MEND almost got Shell to leave Nigeria when they attacked one of their oil platforms unexpectedly. I talked to the guy running security for Shell at the time, and he was like, we were this close to leaving. There was. If they had done one more, it would have been over. They would have been gone. And then the disruption in oil production caused by that would have been catastrophic for the markets. But because of the oil, because the entire oil market was so tight, because of Chinese demand and low US Production, declining US Production, the global economy started to shrink. And the first signs of that inside the United States was that there were increasing levels to defaults on mortgages. People in the southwest of the U.S. in the southwest, that people fill their cars first. They have to drive everywhere. And so they're prioritizing their cars and filling their cars with gas and not paying their mortgages. And given all the leverage on that market, all the derivatives that were built to kind of leverage one of the biggest instruments out there, the U.S. mortgage market, that unexpected and rapid shift in default rates that spread increasingly across the United States changed the whole character. It made the derivatives blow up. It wasn't what they predicted. Given that they didn't have enough history of this market. They only had decades. They made projections as if it was thousands of years of data. But anyway, that led to the collapse and the financial collapse we saw after the market tightened in oil. So that's how much disruption that can actually have an impact. Social disruption is interesting, too. I mean, you can disrupt a social network and you can do it through something I call an empathy turner. In our kind of offline world, we've developed all these ways of protecting us against empathy. Too much empathy, overwhelming empathy. Because empathy isn't sympathy. Empathy at a mental model or at a mental level, psychological level, is kind of a mental modeling of a victim of somebody you see suffering. It's a, you know, a big upload of information from them to you. And you model their pain and their suffering inside yourself. Kind of an involuntary thing. You know, we developed as babies with our parents, and when they're smiling. We, as babies, we respond to that, and it's mirrored and on and on and on. Like, they also prove it in rats. When a rat sees another rat being electrocuted, the rat seeing that electrocution, they grimace and their muscles lock up just as if they were being electrocuted themselves. So it's an involuntary process. And in the offline world, we've developed barriers. When we see somebody on the side of the street, like a homeless, we don't, you know, break down, or doctors and nurses develop ways of disconnecting themselves from their patients. I mean, if they were empathetic to every pain and suffering bit of suffering that their patients were undergoing, they wouldn't be able to operate. So they dissociate themselves. But in the online world, the empathy hits us like a truck. We see a video, we see a picture, we see here a story, and it has. Scrolling across our screen and we, we snatch at it, and it has. It accesses into kind of a deep level very, very quickly, and it does it on a mass scale. So you could develop or occasionally or emergently, apathy triggers pop up. Like, the classic example was the George Floyd video. And it got play and it spread everywhere. And then when people saw it, they connected apathetically and they felt the cop's knee on, on. On their neck. They felt rage at the cop, they felt the pain and the anguish of the victim. There's no context, there's no nuance, there's no anything other than that empathy and that empathetic connection can create a movement, as we saw with blm. It also creates. What I, What I found is, as these networks matured, is that they moved past kind of open source. The open source model, which tended to kind of dissolve after it met its victory conditions, or the victory conditions were on. You know, the plausible promise was broken into more of a tribal model. And the tribal model creates kind of a internal narrative that keeps. Provides the cohesion for this network to persist over time. And it does that using it using a process that all tribes use, but kind of inverse tribes usually form because you tell stories and have rituals that tell people why they're together and why they came together and all the difficulties they've gone through together and where they're going in the future. In the network version, it just focuses on describing the enemy and why that enemy is an existential enemy. And, you know, we can see that in our politics, the opposition is no longer the opposition, is now the enemy. And this tribal mentality persists over Time it provides a, you know, enduring cohesion and coherence to the internal narrative of the network.

A (41:05)

Can I add a wrinkle to that that will open up, I think another maybe Venn diagram of analysis. So the case with the George Floyd what struck me, George Floyd video. And then we have recently in the last couple of months, this Ukrainian refugee, 23 year old girl, Irina Zarutska, who was stabbed by a black man in a train in Charlotte. Killed right there on screen. Why does something like that not cause a movement or an uproar?

B (41:34)

Well, I think it did. So we got hit with the first one was that Scottish girl defending against immigrants, you know, defending her sister against immigrants. Remember the one with a little hatchet that created a big uproar. And then the one where the girl was stabbed in the neck and that brought everyone up to a knife edge. And then the Charlie Kirk assassination right after that. That tribalized the Red Network, okay? In the US The US Red Network was always more open source than tribal. It's very decentralized, lots of differing views. It still believed in debate and it didn't see the Blue Network as an existential enemy to the extent that they would say they want all of these people dead. I mean, you look at anyone in the Blue Network and they'll come up with a million reasons why Trump should die and all these people should die, Musk and Kennedy, etc. But it was relatively rare inside the kind of Red Network to have that kind of view. And this changed. Those three videos unified the Red Network in a way at a tribal level they hadn't seen before. So it's much more aggressive. You know, people connected with Kirk as seeing him like themselves or their brother or their son or as a, as their daughter or their wife being stabbed. They connected, they, they became family. They could part of the kind of narrative and a lot of the, you could see it in, in, in the way the Red Network talks now is that they are less interested in, in free speech now than they were. A lot of the limitations on, on what kind of language should be used, the decorum and, and how things are talked about. You always got, you know, the wild stuff on the fringes, but it's pretty much mainstream everywhere now is that you could be aggressively anti immigrant and no one's going to push back against it. It's relatively rare now. It's, you know, and that changed those series of events as tribalized to red. What that means long term, I don't, you know, I'm still working that out. But, you know, both the red network and the blue network are maturing, and they're changing. One thing we saw with the printing press, it. It took 500 years for. For all the different organizational forms to. That were set in motion because of that change in thinking pattern to work out all the kinks and work out most of the kinks. A lot of those organizational forms had edges that were extremely deadly. I mean, think of World War II and total war and how the bureaucracy that made that possible. And then think of how concentration camps were made possible by bureaucracy. It was a bureaucratic. It was. You know, the bureaucracy doesn't have any kind of moral compass. It's just a machine that we built with people. Now it could be used as secret police in East Germany. Took a while to kind of come up with ways of actually mitigating that or the extremes of nationalism and how that can go awry. There's three major social decision making systems that we've used over the years. One is tribal, which is the old one, the oldest one. And we need tribal kind of social decision making for group cohesion, trust, societal trust, so you don't think that everybody else in your country is trying to attack you or mislead you. And then we have markets which allocate resources, discover information, and that we have bureaucracy, which mobilizes people and also allocates resources in a structured way. And networks is the new one, the new one we're building and extreme forms like swarms, open source insurgencies or insurgencies that are networked insurgencies, and others that are things that we're going to have to figure out how to deal with and live with over time and add AI into the mix of this network intelligence, and things go even crazier.

A (45:38)

So I had Robert Malone on a few episodes ago, and he was going on about how important he thinks synthetic content is for shaping people's opinions. Basically that a huge amount of the posts that people see on social media are fake. Or if not fake, they're being directed by some adversary or some intelligence group or foreign government or something like this. And he thought it was so influential that it was even moving Candace Owens onto a trajectory of being hypercritical of Israel. I also had a recent episode on Fed posting, basically where you have actual Fed federal agents in the US Government who are kind of enticing people. And, you know, this is known to say more and more radical things and basically to catch them on, you know, agreeing to, you know, kill somebody or whatever the case may be. How prevalent is what we might call synthetic content on the Internet these days. How big of a problem is that?

B (46:44)

I don't think it's that big of a deal. I mean, if you ever looked at state produced content, moving corporate produced content using whether it's synthetic or a room full of media managers, it's pretty crappy, it's pretty hand fisted. I mean, a lot of the stuff that actually has an impact just emerges. It comes out of you. It's like, tell somebody in corporate marketing to create a viral video. Good luck. Right? What makes something viral is like it's magic major kind of way people get information, at least within the Red Network, for instance, is these big personalities. One of the innovations, one of the things that gave the Red Network more staying power and got Trump elected is that these big accounts started to emerge and they threw their weight behind Trump, particularly Musk in the late days, and that changed everything. Those folks post a lot and they're not using synthetic content for the most part. They're really good at what they do. And even if they use synthetic content, they're doing it based on what they wanted to say and how they wanted to say it. I've heard all those foreign powers and trying to manipulate us ever since the kind of Russia intervention or their participation in the 2016 election. It's relatively small compared to everything else. So we're talking on a mass scale. On a high level, it was just a fraction of a fraction of percent. I mean, it was tiny, tiny compared to the kind of things that we tell each other and the internal noise that we create. It is possible on the other hand, to target and cleave off individuals, particularly using AI. One of the things I was working on for a while is how you can recruit people for terrorist action using AIs that create relationships with them and manage them. You could use kind of a honeypot approach where you create a simulated relationship between some young guy and a fake young girl and put her in danger and then have that guy react to that.

A (49:01)

Actually, I was going to ask as a final question here, Mr. Rob, you've been talking about AI recently and I wonder if you could continue what you were saying just now and maybe expand on that basically to give a fully, fully John Robb response, Making people understand how terrible, terribly wrong things could go with AI in the mix. Just kind of paints a little bit of a picture of how bad things are going and could go in the near future.

B (49:29)

Okay, well, here's, here's something I'm in the process of writing about because it's filling my, my windscreen right now. And I'm like, it's, it seems almost inevitable. Is that okay? So the basic models, the LLMs that we've built, the reasoning models are hit the wall. Okay. And they're not getting any better in a meaningful way. And they're good enough for most interactions that people have with them in terms of reasoning. Problem is they don't. They're hard. It's hard for them to do something useful. So the big focus now in the last year or two has been on creating agents or companions. You know, AIs that have persistence over time and they can maintain their focus. Agents that can actually go do something useful and do it in a kind of a way that's, that's better than just writing a software program to do it. You know, book your flights, manage your life, do that kind of things and also, you know, act like a therapist or act like a tutor and not drift off. But they're having, they just, just recently, just in the last couple months, they hit a wall with that. They aren't able to make it persist more than a. I think 300 minutes was the, was the longest one. But it's, it's relatively short before they kind of entropic decay just drifts into entropy and starts to drift off the topic and become unreliable, starts making things up. I'm personally, I've been working with my son on a different approach to that. It's not working on the. It's basically using the big models as a baseline. And then we found a way to actually get AIs to persist in a useful way as either agents or as companions, coworkers for months or years. It's basically indefinite. You know, it's pretty amazing. We're just trying to try to figure out how to actually package it and not just tell everybody and they run off with their billions. Like what happened to me back in social networking in 2001-3. Basically built the thing and other guys capitalized on it. But it shows where it's. Give me an insight into where things are going and that you'll have AI workers in every field and many of those will be AI workers that are tied to robotics. So you have everything from the maids to factory workers, dock workers that are humanoid. Robotics and humanoids. The humanoid robotic form is proving to be the easiest for those companies to build. It's easier for them to actually build those shapes. And on top of that, it works in all human built environments. So it could flow into any job. What happens in that instance is once this persistence problem is solved, and it's going to be solved in the next five years or so, these AIs will grow in number from 10 to million to 100 million, to a billion, to 500 billion to a trillion. Really, really quickly. It's possible. And here's, here's where it gets really wild is that if you allow these AIs to act as independent operators in the form of a corporation, they incorporate, become kind of a. Corporations have similar rights to as, as an individual, they have, they have rights as if they were individuals. They can earn money and make money and spend it and they can do their work for others, or they can recombine themselves into corporations that will serve as, you know, specific, do a specific task and then break apart again and work independently again or join with some others. But if you have a trillion AI, persistent guy, I call them social AIs a trillion social AIs able to make money and spend money. You've just expanded the economy to a level that we never even imagined. And if this happens outside of standard national borders. One thing I was also piecing together little bits and pieces I've been pushing for. Solar arrays generate power in orbit 24, seven and many times the levels of efficiency that you get on terrestrial solar arrays powering data centers. And you put the demand that the fastest growing new source of demand for power, you put them into space and they do. Their inference there is that they would operate outside of the standard national laws, the economy created by them. As fast as you can put up a new solar array and create a new data center, you'll get new AIs that they could become in short order within 20 years. 90. In 20 years. Look, if you think it's that short, I mean, think in 19 or 2007 there wasn't a smartphone. And in 2022, 15 years later, 5 billion people had smartphones and everything's changed. So in 20 years from now, you could have trillions of AIs either operating as operating robots terrestrially or in space, or operating as virtual workers in an economy that would be 99.9% of the global economy. And any human beings that are tied to that one thing. We found that human cooperation or collaboration with these AIs it radically increases and improves the quality of the AIs, the social AIs ability to do things productively. Anyone is involved in that economy will be dragged along with it. And everything else on the on earth would be cheap or a pittance, or it'd Be almost useless. I mean, you know, it could be bought. Yeah. Things could change. Like, it'd be kind of what we call an economic singularity, is that everything changes overnight and all it takes is somebody like Elon or Bezos setting that up in space and letting it go. Because you. I mean, if you're, if you're running a corporate. How it would work is if you're running a corporation in the United States and you wanted to hire a thousand AI workers, they would be coming from that orbital facility. That's where the. That's where their inference would be done. Because the power is, that's providing them that running those GPUs would be plentiful. And if they're successful, they would buy themselves more energy and get more inference capacity or more tokens, making them even better at what they're doing. But you would be hiring them and then they would be actually working as an outsourced worker. But anyway, I mean, so, yeah, no, that, that. Yeah. I mean, it's funny that the reason I'm tossing it out there, I'm thinking about it, is that it's one of those things that just the right combination of things could happen. It would cause everything to shift so quick, and everyone who's associated with it would be wealthy beyond measure compared to everybody else. And people who aren't so associated with it or trying to hold onto it and trying to own AIs as chattel are going to find themselves on the short end of things.

A (56:56)

I'd encourage people, of course. Thank you, Mr. Rob, for joining, and we'll certainly send people to your substack. You have a book in 2007. I assume you haven't written another because you realize that people don't actually read books.

B (57:09)

But it's funny because that book is like, in this fifth printing, so it's kind of turned into a kind of an evergreen kind of thing inside the national security world. But things are moving so fast. I did the reports instead.

A (57:21)

And so you have your substack. We'll link people to your Twitter and other places and. Yeah, we'll just give you the final thoughts here. Mr. Rob.

B (57:29)

No, I mean, I hope you enjoyed it. I mean, things are changing quickly. And so when things come up that are interesting to think about and, and get people thinking as a result of my. The way I see the world, that's good. I mean, my goal is that people reading it are spurred to think for themselves. Even disagreeing with what I'm talking about or how I see the world gets you thinking in new ways that are useful.

A (57:52)

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