Episode 22: John Robb on Global Guerrillas and Frameworks to Drive Decision Making

Informing your decisions with intelligence analysis and insight brought to you by the team@ooda loop.com all right, I'm Matt DeVoe, CEO of OODA, and this is the Oodacast. And we're happy to be joined by John Robb, who I've known in multiple contexts over the years. He's the author of an interesting book. We've been Red teamers on several very interesting Red Team initiatives and collaborators, collaborators on research, et cetera, over the years. So, John, why don't we start off by you giving a little bit of a background, you know, where did your career start and what are you up to today?

Oh, wow. Okay, short version. Air Force Academy, astronautical engineering, pilot training, followed by a couple years in C130s and then five years in special ops. Got drafted into a kind of a tier one counterterrorism unit. That was interesting. Got out, went to Yale, got an MBA to kind of reboot and ended up as a analyst at Forrester, which happened to be in 95. So I was their first Internet analyst. They kind of sacrificed me to that, but I ended up lucking out. And so a lot of coverage in the papers and everything for a couple years as every Internet company came through my doors. And then started my first company with some friends, Gomez Advisors, which became Gomez. It's a performance testing network that tested the performance of transaction systems at banks and brokerages that ended up selling for about 295 million, which is kind of nice that you built something that had some lasting potential. Then I got involved in 2001 in trying to build social networking, building on a report I wrote back at Forrester.

And.

Ended up as CEO of Userland Software. And we did the first rss. We open sourced that. And then we built the first kind of blogging network where you blogged and then you subscribed. And it was an open blogging network back in 2001 when no one really got what social networking was. And then Facebook and Twitter happened. Looks like the same interface. Those got big. And then I ended up doing a bunch of other different companies, global printing company, doing software for the military and social networking. Wrote a book after the Gulf War kicked in. Brave New War, which is looking at here. Yep, yep. And that was looking at how warfare was changing. And we're seeing open source networks applied to warfare. And that ended up being pretty prescient in terms of, you know, describing how Iraq was operating. And then since then I've been doing a variety of different things in writing. I, you know, been doing a blog on warfare called global guerrilla since 2003 that went and became the Global Guerrillas Report three years ago. And so I put that on Patreon to kind of winnow the crowd down, to kind of make sure that the people that were interacting with me on this were high quality, and it's proven to be such. And been tracking the intersection of politics, technology, and warfare. And it seemed to be right on the mark because that's, you know, the stuff I've been writing about is exactly what we're dealing with today.

Yeah, excellent. Let's rewind. I definitely want to get into the Global Guerrillas thematics and we'll put a link in the YouTube comments to make sure people can find that easily. So transitioning, working tier one folks on a counterterrorism mission into an MBA program, kind of, what lessons did you take that allowed you, from the military experience, to transition into the business world?

Well, I mean, being in a Special ops role is really different than the standard military experience. You operate as an outsider. I mean, you're given, I mean, no one's given like an aircraft and a bunch of cash and go out and do stuff. In the regular military, it's very controlled. You have to call before you take off and after you take off, and then you get en route, you get a call and then after you land. Not, you know, not the case in Special Ops. So that made the transition to kind of entrepreneurial thinking and entrepreneurial life much easier. It was looking, always looking at business opportunities from. As an outsider. That worked out good when I got to cover the Internet because I was already thinking as an outsider. And so much of what was happening on the, in the Internet space between 95 and 97 was, was all about trying to break things from the outside disrupt. And every company had a disruption message. And that startup fever was definitely up my alley. Things that transitioned over, it's just commitment and the same kind of work ethic that you have in the military. You know, applying to business, that worked out fine. What surprised me, though, is I got into finance and got into the entrepreneurial space. In the tech space like Silicon Valley, I didn't find any ex military folks. I mean, very, very few. They're thin, thin on the ground. I thought there would be a lot more of a, you know, contingent maybe in finance and not the case. I'm surprised that most people just stayed in the beltway area. They kind of graduated into, you know, consultancies that were going to the airlines. In my case with pilot piloting. All my friends are, you know, Airline pilots. So it's a, it's, it was, that was surprising. I, I think that, you know, the military guys that I saw that transitioned into finance did really, really, really well, I mean extraordinarily well. And there was lots of opportunities for that kind of mindset, military mindset that were unexploited.

It's interesting. I definitely see that in my interactions with some of the private equity and venture capital firms. There's a role for some of the military folks transitioning in there, especially coming out of special forces entities seem to recognize the value just in the ability to operate in the critical thinking and the kind of leadership associated with that. Being at Forrester in 1995, are there some things that strike you as interesting that you saw that represented a groundswell that you thought were going to be really important? Because that is really early days in the commercialization of the Internet.

Yeah, I mean I didn't really, I mean I didn't have a background in it, which made me kind of an outlier in Forrester. And Forrester had been going sideways as a about 20 million dollar company for many, many years focusing on those core IT subjects. So they allowed me to be creative in terms of trying to synthesize frameworks for understanding how this fast moving situation was developing. And these frameworks, it's an interesting thing is, you know, when things are changing so quickly, there's really not any time for considered analysis where you take, you know, build these, do this extensive analysis and write 70 page reports on it and really dig into all the details. What you need is a framework. And I found that decision makers at virtually every company during that period, 95 through 97, were floored. They didn't know what to do. They were paralyzed by the Internet and what was happening, what was coming. And what I tried to do is develop frameworks. What I'm doing now at the Global Gorillas report is develop frameworks for understanding or parsing the news as it's developing. You know, there's like pigeonholes for where you could put, you know, different news items in. For instance, I wrote a report on what I called navigation hubs in early 95, just before the portals went public. And I said, okay, these guys, I ranked them, you know, from Yahoo down down are the going to be the, you know, centers of the Internet. And they're gonna, every content provider is going to need to slot in to their hubs in order to make money on the Internet. And that would help people, you know, get their heads around the emerging situation in a way that allowed them to act and some cut deals with Yahoo and different portals that allowed them to gain a full hold on the Internet. And then I wrote a report a little later in the year on what I called personal broadcast networks. This idea that we would be publishing, everybody would be publishing onto the Internet, pictures and text and the like, and then we'd all be subscribing to each other in this big network. That was a thought piece. And I had the guys at Netscape and Microsoft come and say, ask me, how do you build this thing? And I go, I don't know. I mean, pointcast may be a good example of an early instantiation of it, but it got people thinking at least along those lines. It took me four years or five years to find a company actually building it, Userlab, so. So that's what I try to do. Sometimes it's like long term, something like the personal broadcast networks or something short term for decision makers to unfreeze them, unparalyze them so they can act and interact with a fast changing environment.

I love that dynamic of leaders not being able to act because the environment is changing too quickly or they feel like they don't have the data points. Do you think that the pace of change has been increasing steadily over time, or are we seeing today the same types of paralysis that you were seeing back in 1995-97?

I think it's worse now. We're getting a rapid technological change and in addition to that, we're getting rapid social change, rapid political change. It's paralyzing. And not knowing what comes next, you know, makes it impossible to plan. If every bit of news that you, you get is a surprise, you're, you just, your natural tendency is just to sit there and wait till the news settles down. Or, you know, you could start to make sense of what's, what's happening before you act and no one wants to act, then find out the next day that they've taken the wrong path. It can be fatal in this situation. You can be mobbed and swarmed. Yeah, go ahead.

No, I was just gonna say on that kind of the pace of change and that inability to act or creating frameworks. Are there some frameworks for what we're seeing today that you think are useful to help people decipher kind of the global environment that we're in?

Yeah. One thing I've been working on is I've taken the open source framework that I used in warfare and moved it to protest. We saw that happen in the Middle east almost a Decade ago, not quite. But it's also being proven useful in this current context. It's changing the way we conduct politics in the United States. And what we're seeing right now is the emergence of a new decision making system. I call it network tribalism. And it's proving to be very powerful. Where, you know, a network forms online and it's open source in the sense there's no, you know, set leadership and there's lots of people contributing to it and they get focused on a single idea and they push it forward, they make it happen. I mean, we saw just recently, you know, shut down the economy in response to Covid. I mean, it was the individual actions of tens of millions of people that really did the heavy lifting on that, more so than what the states did with their shutdown orders. And it's keeping it in place now, even after the shutdown orders have been lifted, people are still staying home. They still don't think it's safe. So that's kind of. This network tribalism is very powerful. It also, you know, when it gets focused on an issue, it can take to the streets. We're seeing that as it's taking to the streets around the country, focusing on getting control of police forces and kind of equalizing the power balance between the public and police. Yeah, network tribalism is to put it in a larger frame. I used David Ronfeld's timmin. David Ronfeld from netwars fame, he was at RAND for many, many years. He came up with a framework for understanding how things are changing over a longer time period since, since, you know, 500 years ago, is that we have these big social decision making systems, which is right up our alley with the Buddha. Right? Big social decision making systems.

And.

Before the printing press and the Reformation, it was feudalism and a universal church. What we had since then is the nation state and bureaucracy and markets. He says, okay, there's three decision making systems that we currently use in society and we refine them and made them viable. It was bureaucracy, which is great at mobilizing, it's great at executing on plans. We have markets great for allocating, discovering information. And then tribalism, which became nationalism, which gives us cohesion because we have to have a certain level of cohesion in order to operate as a unit. If you don't have that cohesion and you treat, if your countrymen are now enemies, you don't trust anything they say. And what we're adding is now a network layer, you know, fourth. But what I think is happening is that network layer is now replacing what was tribalism, what was nationalism and patriotism supplanting it. And it's putting pressure on bureaucracy because it's making decisions faster. It makes decisions faster in terms of COVID than the bureaucracy does. The bureaucracy seems to be faster, flailing and that it's more powerful than markets. This network tribalism is more powerful than markets because it was able to shut down the economy through the actions of tens of millions of people changing their demand for products and services, not flying, not taking vacations, not purchasing things, not going to restaurants. Network action is proving more powerful than the market decision making system in that regard. So learning to understand that and there's lots of nuances and lots of interesting things that can be added on to that. I have plenty of reports that I wrote about in regards to this and looking at it from maybe the international stage too is, you know, how does this networking concept apply to places like China? And in China, where they're actually the state is taking control of this network decision making system and then enforcing its use. And from the social credit system that they're doing to getting all the companies and everybody to express publicly online that they're aligned with the state's actions. This is a pretty cool space. It's a framework for understanding it. Once you start to read it and start to get it and every bit of news that you start to get now starts to fall in place and you can put it in the right categories, it makes it easier to make sense of it and then it makes you feel better because at least you have some knowledge of where things are going.

With that, do you have to have the awareness with regards to how adversaries might try and impact that network tribalism? Because if I went to a town meeting, it was my neighbors sitting next to me. Now if I'm participating in this network version of it, there are also adversaries and folks that don't share the same geography that might try and influence that. So how do you protect against that external influence component?

Yeah, it's hard. But in the case of the US and US is probably alone in this. I think the volume of what we produce internally is so great that it kind of overshadows anything that China and Russia can do. It's just they're lost in the noise. Now if I was a smaller country boy, it can make all the difference in the world. Manipulate Facebook in the right way. You get places like the Philippines with 90% of their news they get through Facebook. That is like a place where you could really have Serious amount of influence if you're an external player with some smarts here in the U.S. not so. You know, we're kind of developing this an open decision making system and it's messy and it's loud and there's so many dissenting voices and it's so hard for anyone outside to even be heard. They could spend a hundred times what they're spending now and it would just be drop in the bucket compared to what we produce is just a byproduct of our internal discussions.

So it seems to me the most important thing that you just talked about with regards to developing the resiliency. I get the volume aspect of it, but the counter voices, the dissent and not sharing opinions. Because an analogy I used to use that's still in play is in some cultures in Africa where we're rapidly introducing Facebook and other social networks and in fact they're building the network for them. So obviously that's kind of the first source of content that they consume. They didn't have the way to discern a picture is not being real. Right. To them, photography was something that couldn't be manipulated. So you saw where they were very, very effective info op campaigns early on where the population, it would be something you and I would recognize as a really bad Photoshop that was actually influencing the decisions of the population. Now I get concerned because I consider myself to be very well versed in information operations, psychological operations. There are content that I encounter every week that I am having a hard time discerning the reality of it. Right. Without a lot of research. And the cheat, the way that I cheat on that is I wait to see the dissenting opinion. I wait to see the person who says I know this is Photoshop or digs up the photo of Hitler in that same pose, not holding a Bible. Right. I mean, so it seems like there's great power to the network to be a little bit self policing in that regard.

Yeah, I agree that we're learning to leverage our network. I've made the case that we're only as smart as our network now because you can't do all of this. You can't verify the information effectively alone. You can't work through a lot of these topics that we're dealing with alone. You have to do it with a group of people that you trust, maybe even not trust, but that they tend to have high quality contributions. But yeah, building a good network is key to surviving this. I mean it's part of goes Back to Marshall McLuhan. His early stuff was amazing. In terms of how electronic media is rewiring our brains, it's changing the way we think. And because it's changing the way we think, it's going to change the way we organize society. He was maybe too early when he was saying it in 60s, but now it's right on target that we're becoming more tribal in our thinking. And that's. That's unleashes a whole set of problems, but also opportunities. The problems being that we tend to focus on every single little action of everybody in the tribe. You know, they take the video of that person saying this and it blows up and everyone's like pointing the fingers. It's just like it. If it's like the. The old lady in the village who knows everybody's business and if something. Somebody does something wrong, everybody kind of piles on it. Also can set up situations where we all think the same thing, you know, hyper consensus of sorts, and then we act as a unit. And that can be pretty scary. Like we're seeing it with. The COVID response initially was good, did the job. It blunted the spread of COVID in the US but getting out of it on the back end, whether or not it's the right time to do it, is getting people to re engage with the economy and get out of the siege mode. That consensus thinking mode is going to be really, really tough. We just don't have the tools for that. You know, the bureaucratic tools are just not available. I mean, you know, thinking in terms of maybe giving people, you know, everybody a stipend of money over a course of a year or two, you know, a thousand bucks a month in order to get them to start spending and start re engaging kind of a whole population, you know, paddles to the chest, kind of up. Might work, but our bureaucracy couldn't even get their heads around something like that. It's just too outlandishes. It doesn't work for them.

Yeah. So there's two kind of divergent threads I want to pull on there. The first is, you know, around the tribalism aspect we saw particularly around Covid. Right. You talked about the individual decision making on the network. I would say kind of the next year of decision making was kind of in the corporate domain and then the last was in the government space. Right. We had a lot of corporations that were acting before the governments. If we put kind of like a sci fi hat on it, you know, this idea of for, you know, like Cory Doctorow, you have a tribe associated with the time zone that you're in or a Bruce Sterling or Neal Stephenson, where you start to have more affiliation for a particular company than you do for a country, you know, organized in a national construct. Do you think that issues like Covid help reinforce or drive us more towards that kind of corporate affiliation, or is that just a science fiction pipe dream?

I'm seeing it more at the macro level. You know, macro tribes. At the national level, we're seeing tribe development. I haven't seen so much development at the corporate level where the primary loyalties are now to companies. I would have thought it would be, you know, something that would pop up as a result of this, but I'm not seeing it. People are, you know, more focused on what we're doing at a national level and trying to align their actions with everybody else. I think it has to do with, you know, one of the ways it changes the way we think being, you know, becoming part of the network is that we've become pattern matchers more than we were, you know, solitary literary thinkers. We used to get a book or read an article, and we read it in isolation, and then we acted based on that. We formed our opinions based on considered reflection. Now we're pattern matching. We're grabbing bits and pieces of data as it flows over us. We're letting most of it just flow past us, and then we're setting up patterns. And the more dominant patterns that we're working on are the big national patterns. Occasionally there's pattern mattress that kind of cleave off like QAnon and. And others who create those conspiracy patterns. They never really get that big, but they become very tightly woven and interconnected, and everyone spends it their entire day grabbing bits and pieces of data to stick into that pattern. Is it possible that companies could do that? Perhaps. I think it's more focused right now is whether companies are aligning with the.

National.

Pattern, the national kind of tribal consensus of sorts. Can you see it in China, where they were looking for alignment? Kind of the big challenge of the 21st century for nations is to stay cohesive. Given how complex and chaotic the environment is, it will tend to rip you apart. As we're saying, they do it by having the state run the network and forcing companies to all align in the states. We've let it. We don't have the government dictating that. And what we have is this tribal network emerging online. And it's trying to get all these companies to align, kind of express that kind of fealty to it towards the network and enact like in the case of the big platforms, censorship of the platform in the way that conforms to the needs of the, of the tribal network or you know, enacting policies and the like that, that align with it. If you don't, then you could end up as the kind of the target of this network and they can take you down. It's very, it's very coercive. It's, it can be, it could, it could be fatal. In the street, for instance, in Hong Kong, they were trying to set up a alternative network where they had the alignment of companies in Hong Kong with the protesters. And what they did is they marked the shops and people knew the shops that were aligned with the protest. So they didn't vandalize those locations. And the ones that were aligned with the Chinese government, they vandalized. So has a, you know, we see a little bit of that in the States with the black owned business or I support the protests on the front window and that gave you a little bit of protection. But it's that kind of everyone's trying to signal the alignment in order to avoid damage. It's interesting, even the shop owners in the US who had their shops destroyed, even after the fact, they would say, okay, I agree with the protests in order to keep their alignment intact even though they had their whole world turned upside down. So alignment, that's going to be a big thing to process. As a business owner, who do you align with?

And the tides change quickly. Right when we talk about Facebook Going into COVID 19, they've got all their employees working from home. They gave them $1,000 extra money to spend. They put $100 million grants into local businesses so that they would be sustained. And now what is everybody talk today? It's failure to censor the president on the platform. Very quick reversal. Just over 60 to 90 days. I do want to talk a little bit about COVID and you talked about surprises and predicting surprise and having a framework for how to deal with it being the essence of being able to make decision making. You and I probably sat and we've done so many red teams, I can't remember which ones we were together in or not. But post September 11, there are quite a few that were looking at these issues of biological disease spread and responses to that and how it plays out. Yet it seemed to me you fast forward 15 years later and we seem to have lost the needle on understanding the risks and the responses and being able to make decision making. Is that just a failure to sustain the cognitive infrastructure behind some of those things that we studied or how can we best enable future leaders to be able to make decisions based on past analysis?

I guess. Okay, so yeah, that's. How do we improve the decision making capability of the bureaucracy? Most of the problems that we had with the COVID early on were because the bureaucracy that planned for it was planning for a slower virus. They weren't planning for a 21st century hyperconnected virus where, for instance, the FDA gave the CDC monopoly production rates on the testing. Okay, so they were focused on quality because quality was more important to them than anything else. Because they didn't want to give people the wrong results. And rather than just trying to get as many tests out there as possible because this is about to hit us, there's no way to kind of do this in a controlled way. Well, that cost us because then the CDC failed and they were a single point of failure and then put us back behind a month and by then it would, you know, all the casualties we have are largely a result of not knowing that we even had the virus because of lack of testing. Or, you know, thinking in terms of only shutting off travel with countries based on considered reflection and deliberation that you could actually slow the transmission of virus from one country to the next by slowly turning off country by country. Well, in this age, it takes five seconds to reroute yourself around the blockage and then you're in. And what you need to do is shut everything off, shut all the borders and the countries that did the best on this, everything from New Zealand to Taiwan to Japan to even South Korea, because effectively it's an island, turn themselves into islands. They shut off connection very early on and stop the kind of ongoing inflow of infection. We've never really done that. We still haven't done it.

Sure.

So changing the way the bureaucracy thinks is tough because they thought they were doing the right thing. Even the PPE production, they thought they had time to ramp up production. Granted, they hadn't been watching the needle on our PPE production go down to 5%, which was a disaster at a national security level. Only 5% of the stuff we needed was produced here. But they thought they had months to ramp up to aggregate the stores that we did have. Also, there's problems with the way that the bureaucracy made decisions is that they took a kind of I know better than you attitude, and that was just fatal in this environment where information is so prevalent. Yeah. Like telling people back in March that masks don't work. It's just nuts. It's absolutely insane that anyone who kind of would Say that masks don't work. I mean, hundred years of infection control in hospitals, you know, masks, everybody uses masks. It's just matter of course. And to say to the public just because it was, they thought it was a noble lie, right? That they would say that to the public because they wanted to save masks for the frontline workers, first responders. But people saw it as a noble. They didn't see it as an noble, they saw it as a lie. They saw it as incompetence. And we have examples of that again and again as time progresses. You have to be upfront, you have to be collaborative with the public in this kind of environment, you have to solve problems together. You know, it's just like another failure. CDC didn't lost control of the testing numbers by mid March. They stop collecting because they couldn't collect from every single state. They didn't have the people allocated to do it. They just gave up. And we had to have an open source effort come out of the Atlantic. Reporters, you know, they started it to gather the testing numbers for the entire US. Can you imagine that? I think there was a kind of a lost opportunity here is that, you know, we had the White House talking about what they were doing for a couple hours and it was off on different meandering things that they decided to talk about is that we had a chance here to run some counter programming for this consensus. All these 100 plus million people who are interested in trying to do something today for solving the crisis. Back in March we could have started this two hours of YouTube programming where we're focusing on solutions. Forget the politics. What do we have to do next? Oh, we have to produce masks. Okay. We don't have enough masks for first responders. Let's produce cloth masks. Okay. How do we, how do we check on this and this, you know, how do we get resources that we need to do this project? Let's set up a committee to do that and here's the website to actually get that done and then coordinating it using this national broadcast every day. And that would have given us a focal point of, you know, like we're actually getting things done and solving this together again, you know, waiting for the government to tell us what we're going to do and how they're going to solve it for us is not the way we should be moving forward.

Yeah, that's interesting. So you'd say kind of one of the biggest impacts was just failure to predict the pace at which it was moving. Right. So the planning process was a little bit More drawn out, vice accelerated.

Right. I mean even inside China, I mean, I don't believe the Chinese numbers. Second, because they got it over to a hundred plus cities by the time they started their efforts. So there's, you know, Chinese death numbers. There's no way that they, they had those numbers, those results. But just difference between when they had SARS in 2000, what, one or so it, the amount of transportation had grown fourfold between then and now inside China and China to the rest of the world. So people were so much more mobile and the fluidity of that movement was so much greater than any kind of models that we had from the 80s and 90s or even the aughts. One thing I found from looking at so many epidemiological models and how people put them together, thought is that those things were filled with assumption errors and old ways of thinking. Like assuming that if they called for social distancing, only 10% would comply. Like what we're getting 60, 60, 70% compliance. I mean Massachusetts never even had a formal, you know, it was all voluntary for shelter in place orders. So. And we got virtually complete compliance. So, you know, those models are useful, but they're often, you know, we're not, we're not going back to these models and trying to update them based on the evolving circumstance because in a complex world, in a complex environment where you're getting hit by a complex threat that leverages these networks and leverages that complexity, you have to rework your models, you have to look at which factors are actually most important and find those factors and then build a new model based on those or update all the assumptions that go into the existing model based on your experience. And it has to be done quick or you're going to be left without any forecasting capability.

Yeah. So what it's calling for is the dynamic decision making. Right. The essence of the OODA loop. It's not make a decision and you're done. It's make a decision, reevaluate. Make a decision, reevaluate. We saw a lot of attempts at very static decision making. This will be the truth. This will be the plan for the next six weeks, when maybe in reality we could have been working at a little bit more accelerated cycle there. Yeah.

In a complex environment, everything, the tendency of the whole network can change overnight. You think you're doing one thing and then all of a sudden the world changes and you're out of step. Or based on the way you've analyzed the current environment, your plan should have this result. But it Doesn't. Right. So what you need to do is you have to do a lot of probes, you have to do a lot of trials, find out what works based on hidden factors that you hadn't considered, and then reinforce the one that works and build up on that. The tinkering approach that we see so often in open source, that works really nicely in this environment. And then there's a more formal process for actually doing that within companies, which is pretty useful, and then also being willing to be flexible, revisit your assumptions, revisit your models, look for new factors, look for new patterns. That's new frameworks for understanding what is going on. What's really plaguing people, if you boil it down to, from OODA perspective, is orientation. And I always thought orientation is the key to the ooda. It's the most important piece, in fact, that could be blown out. And there's probably. There's many attempts to try to do it, but it's really hard to do. That's like the combined. It's everything that you are points you in one direction or another. And what we're having right now, given the pace of change and the way things are changing, you know, entering a completely new environment, is that our orientation? It's an orientation crisis. We're not. All our experience and all our training and all our organizational structure is geared in one direction, but the reality is pointing us in another. You know, the opportunity space is in a different direction. And you have to. You should orient to what the environment demands. You know, it's not orient to what history taught you. And orientation crisis requires new frameworks, and that's what I would try to build.

So talked about network tribalism as being a useful framework. Are there others that you would highlight, you know, that would be useful for people to be considering right now?

Oh, wow. I did a lot of stuff on AI, did a lot of stuff on McLuhan, dug into the different modes of. Of kind of a political, sociopolitical warfare, moral warfare, online, disruptive warfare kind of maneuver based, kind of more what the Trump does. Fast transients, rapid disruptions, and how those all work. And if you understand that, you can make sense of Trump in about 10 seconds and you can make sense of the counter pressure in terms of how they think and how they operate. More warfare works in a specific way. And it works in a specific way online. Yeah, so many. I mean, I have a lot of frameworks. It's just that, you know, I could probably fill multiple podcasts getting into each one of these Things excellent. But yeah, you know, pattern matching, how it's changing the way we think, how that. How empathy plays into that. Because a lot of this tribal formation is based on shared empathy. And a lot of these videos and pictures you get are supposed to trigger an empathic response. And the extreme versions of that is that. Is that extreme empathy can lead to those violent pop offs that we see. I mean, if you read the kind of those white nationalists that went and shot up different locations, all their writing was extremely empathic, but it was selective empathy. You know, my people are being killed, and I can't. Can't stand to see this anymore. You know, we're being crushed. You know, all my family and all my friends and everybody I know is being. Being destroyed by this environment. I have to act. But it would. It's no care for the people that are killing. You know, it's. You remember the Apocalypse Now?

Yeah.

Colonel Kurtz was saying, oh, you know, he wish he had soldiers that could be barbarians during the day and then come home and be peaceful at night and kiss their wives, kiss their kids good night, and not be bothered by it. And those tribesmen were able to do it, but he couldn't get his western soldiers to do it. That's all done through kind of this selective empathy. People outside of your tribe are not worthy of empathy. People inside your tribe get all of it.

Interesting.

Yeah. When you tell a story to a tribesman, they put them. Empathy is kind of isn't what we think it is. We tend to talk of empathy as kind of a voluntary action. It's actually an involuntary modeling because your brain is modeling the person you're empathizing with. You get similar facial expressions. You get similar tenseness in your body. If they're under attack or they're describing that they were under attack, it's an involuntary process and triggering that if it's properly triggered, that means that you're empathizing with that person. That means you're. If you. If you do, you're connected, you're part of the same tribe. And like a sociopath can fake empathy, but they may not have had the involuntary triggers when they were young and then they became developmentally kind of disabled. It's an interesting. It's a whole, you know, how that works online and how those, like, pictures and videos you get and how, you know, people are saying, can't you feel my pain? Kind of thing. Can't you see how this is, like, egregious? What we're seeing right now in the big protests are all calling for empathy. Empathy being the key to building the new narratives for a tribe. Tribes are found around tribal formation is, you know, we have a shared story about what makes us unique, what things we have, adversities we've overcome and why we're better together than apart. And those stories are communicated through empathy. I identify with them and we're getting those stories right now through this network. I identify with this man, identify with the things that need to be done. Problem with that, of course, is that the people outside of that tribe you can lose all empathy for. So, I mean, that's just one little. This is one little framework. And it's just. It's an interesting way of kind of understanding what you're seeing every day. But I think I went down a little bit too much on the Rabbit Hole on that one.

It's all good. I think you're fine. We got the folks that watch these episodes, they like going down the rabbit holes. At least that's what we found. I'd love to talk a little bit. Given that you've been so prescient on kind of emerging threat environments, what do you think are some of the emerging threats that we face over the next five to ten years?

Oh, I mean, externally or internally?

Either.

Yeah. I think we're going to be pretty focused on the internal dynamics and getting this right. I mean, hammering out how to use network decision making is going to be traumatic. It's already traumatic. It's gonna get worse. I mean, just think of it. Is that going from feudalism in the universal Church in that way of thinking, it's a completely different switch. When you start to go to the nation state, you start to use markets and you start to use, you know, nationalism as a mechanism. And those didn't appear overnight. They weren't kind of there. That switch out of that old mindset to the new mindset ripped apart. Germany and probably 30 years war is probably the bloodiest war in European history. And that can be traumatic. So I think most of the stuff that we're going to deal with is internal. Hopefully it doesn't end up like Germany during the thirty Years War, but there's always an outlier situation where that can happen externally. I think most countries are going to be dealing with something similar or they're going to go through a kind of a lockdown phase like China's doing. They're locking everything down using networks. I call that the end state of that. When you start using social AIs, which are the biggest AIs that we've developed so far and put into play to kind of enforce social cohesion could end up becoming kind of what I call the long night. If that propagates, if China is able to export that or people copy that and that becomes the dominant approach, we'll have kind of a long night of oppression. Because it doesn't just watch what you do publicly. I mean, it can get into every single private communication and. And change that, alter that, or censor that and use that against you. And then you add sensors and you add all this other stuff that we're surrounding ourselves with, and it becomes the ultimate nightmare. Interesting.

So it's kind of. The AI used to invoke that because the AI is the only thing that's gonna have the processing power to basically put, you know, put all the pieces together.

Well, yeah. I mean, if you want to censor the community, the private communications of a billion people, you have to have an AI. Yeah, but we're going to train them. I mean, we're constantly finding the exceptions to things that pop up, running it by human filters, and they're trading AIs, and that's a constant process. So much of what will constitute new jobs in the future will be that human feels the new thing. They develop a response to it. And that goes into the AI, just like an Uber driver, you know, their response goes into their AI. And we can do that with every profession. It's like everything that we do is going to be set up in that situation or that kind of process.

Yeah, we gave. We just did a Oodacast with Peter Singer, with August Cole. Just wrote a book called Burnin. And I don't know if you've read it yet, but the premise is.

Oh, yeah, I got an early copy of that. That's good.

Yeah, as did I. I mean, so, you know, I mean, it a AI robot that was, you know, paired with a law enforcement official for this process of kind of teaching it how to operate. You know, for me, I love the plot. I mean, it was a lot of fun. I love the look at technology, and I love the fact that the technology was all based on stuff that exists today. But what was really fascinating for me were those sequences when the FBI agent was actually training the AI.

Right.

Do this, don't do that, you know, in the future. And its ability to kind of, you know, input that and adapt its behavior on the fly based on the new parameters was kind of fascinating.

Me. Yeah, I'm not a. I'm not. I mean, I love the book and I love the whole interaction But I think the main course of AI won't be towards humanoid. We tend to think of it as kind of a human replica. I see it as the word the AI is really going to take off. And it's already taken off is in this kind of. It's not human, it's kind of a symbiont. It's like the social AI that we interact with every day on Facebook and Twitter and Google and Amazon. Those things are. They don't look human at all. And they're interacting. They're kind of living in the space between us as individuals. They're mediating our interaction. And to think of them as that is trying to get inside our perceptions to kind of influence us at a deeper level. That's a different thing entirely. It's not humanoid in any way, shape or form, but it doesn't live without us. It's kind of a thing that we swim in. But it's living in a sense, but it doesn't look human and it doesn't act human. That is going to be the dominant form of AI.

Yeah, the AI as part of the infrastructure as opposed to something we personify.

Yeah, but it's a living interaction with it. You know, it's like a living infrastructure because it lives between us and around us. And it's not the kind of robot that sits across the table from us that we're trying to teach and the.

Machines are, you know, or the AI is even more empowered day to day because I know, like on Facebook and Twitter, I mean, they control what you see, you know, to a greater extent every day. I used to have. I used to have lists of people on Facebook that I would want to say, like, I want to view this list and I want to just view it in chronological order. I want to see everything. I want to see the raw stream. And it's incredibly difficult to get some of those feeds in raw stream format. Now you have that level of AI.

Interpretation happening everywhere, Right. And yeah, that's. That's the downside of these AI projects. You know the paperclip maximizer problem, Right? Yeah, yeah. It's a. I mean, and we see that happening all the time at the big. At the big tech companies now. Like the paperclip maximizer is this idea that if you set a goal for an AI and they iterate towards that goal, the way in which they achieve it could end up being fatal. In the case of giving an AI the opportunity to, or the goal of trying to maximize the production of paperclips, they end up Growing and learning how to acquire new companies and then learning how to defend those companies and acquire new resources and then taking over the world and burying it in a mile deep of paperclips and then go into space and on and on. In Facebook's case, it would be trying to maximize stickiness on the site. They amplified the stuff that was most volatile, the stuff that's most inflammatory because people stuck with it, I mean, or in YouTube, you know, they, they bring you down that kind of, you know, rabbit hole. And sometimes and oftentimes that's an extremist rabbit hole.

That's a great point. We probably have had AI provoked deaths or killing. We just don't know of them yet.

Right.

Because we don't understand the way individuals were influenced by those platforms towards a set of behaviors.

No, they don't eat. They don't either because those, there's no algorithms to look at. I mean, they're black boxes, they're neural networks. So, you know, as it iterates, all you can do is to kind of evaluate the effectiveness of an AI. I mean a deep learning based AI, which is really the only method that we found that actually achieves some superior results is to look at the outcome and test it. Kind of like if you were, if you had an AI pilot, is that you give it a check flight and you put it through as many maneuvers as possible and look at the outcome and it, it's not like you could do with it with a missile, a guided missile and you could check subsystems and drill down on things. This is more of a qualitative analysis. Right. And qualitative analysis is that does this work in the real world.

And one of the hardest fields in AI right now is explainable AI, right. Getting the opportunity to understand the decisions that it's making or how it's being influenced.

So yeah, human. Yeah, I don't think as well any more than you would be able to get a human being to explain all the influences that made them do what they do. I mean, you train up somebody and then explain how you came to this decision or that's really. They don't necessarily know why they came up to that decision. It was just an interplay of factors, experiences. More complex the task, the harder it is. So I tend to think of it as a, the same thing as you go through with training a human being or really simple is if you're training, you're teaching a kid how to catch a baseball, they're not doing physics and they're not doing math. They're doing a complex neural net calculation is that, you know, where the trajectory of the ball, how that works, how to catch it with your hands and how to do that successfully. They can't explain it. Again, explain how they did it and it's a black box. And if you did the same thing with it with a deep learning AI, and they're not going to be able to explain it, and I don't know how much the explanation would benefit you.

You know, I mean, that's true.

Yeah, right. It's just.

I like that analogy. Yeah.

Yeah. Look at the results. Test the results. If it works, most times you're probably there. And these AIs tend to be pretty robust in regards to, you know, a lot of the little things that would normally set off a human engineered system. No, they tend to overlook them. And in the human engineered systems, you put in a little error and it can cause cascades of failure. Oh, I, you know, you know, the robot that stops because you're the pee on the floor in front of them, that kind of thing. These deep learning link AIs tend to just barrel through regardless. They're, you know, less, less prone to that kind of thing, at least from my experience and what I've read in terms of talking to people too.

Excellent speaking. Speaking of reading, what are some books that are kind of on your, you know, recently read list that you'd recommend for the folks in the audience?

Well, I did Vernon. That was most recent. Yep. And then, oh, Delta V. I would recommend that Suarez. Yeah, that was probably the best kind of asteroid mining, you know, space book I've seen a while. And it makes a great case for not colonizing Mars. Is that it? Just no matter what you do to it, it's still not Earth. And if it's not Earth or even closely approximating it, so not worth doing going down that gravity hole because it just won't fit us. Yeah, those are the top two I think would appeal. You know, I do, I read a lot of stuff. I mean, I'm reading a lot of science fiction, obviously, and so try to stay ahead. I game too. One of the things I got out of gaming, I do kind of classic Skyrim and I modded it. And you know, you can mod everything. You can mod it in an incredible detail. You, you can change the environment, you can change how people interact, you can change the clothing, you can change how you fight and do all this. It's moddable to an infinite degree. And mods come in at 15 a day from a huge community everyone's solving a little problem. And it kind of got me mentally ahead in terms of thinking about or how to think about what happens when you get ar. Because ar, I mean, as soon as you start to be able to do you modify the visual environment and auditory environment, anything's possible. I mean, it's like. I mean, we're worried about fakes and stuff, but I'm thinking more in terms of changing the entire environment, changing how everybody looks to you. You know, not just the info, not that. Just the kind of digital information that comes in or the alphabetical information, but, you know, is what. What the interior of your house looks like, what the interior of your office looks like, what's the kind of sounds in the background. And I mean, everything is model. Yeah, right. If you think.

Absolutely.

It changes it. It changes everything.

I did a, you know, kind of a start of a novel over a decade ago where, you know, the focus was on augmented reality. And that was. The piece is like we could be in a bar and where a TV would be for me is playing cnbc and for you it might be playing the football game. Right.

Like it's.

You people start to modify the reality that exists around them to kind of suit their own needs.

Right, exactly.

It also diminishes the necessity of a lot of technologies. Right. You don't need the screens. That becomes a screen on demand.

Exactly. And I mean, it can fragment in terrible ways. I mean, if you think of it as layers, you could have a Nazi layer. So everybody in that layer is all seeing the world from a Nazi perspective or seeing it from a communist perspective or seeing through any kind of horrible thing that you could possibly have imagined. And they build mods to do that. Right. And then there's this fragmentation of humanity that results takes place. Yeah.

I call them. I call them the OGs and the non OGGs. Right. Because I expected there would be an inherent conflict between the people that choose to live in the augmented reality even and the folks that choose not to. Right. That just want to. Want to interpret reality as it's coming in natively.

Yeah. I kind of. I. I was writing some fiction on what it would be like if you created kind of all the kind of classes you get in the kind of dd, DD classes or superhero classes. And it was done through AR when everyone's using ar because it's so much more engaging than regular life. Regular life look drab in comparison until you have this enough. All this extra data and color and sound and would be so much more is that you could build almost all of those classes inside of that perceptual layer of people. I mean changing people based on and giving him superpowers based on giving him information in the right way at the right time and giving them power to influence what other people see, hear and taste and that kind of thing. It was kind of a cool thing because you actually could see it happening, see how this, you know, all these classes actually played through.

Yeah. Fascinating. Well, this was a great conversation. I really appreciate you taking the time.

Oh my pleasure.

To chat with us and we'll definitely link. I would encourage folks to check out the Global Gorilla site and Patreon site so we'll make sure there are links to that below. Thanks. Thanks again so much for joining us.

Oh my pleasure. Thanks for having me on.

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