The Best of 2024

Danny Crichton:

Hey, it's Danny Crichton, and this is the Riskgaming podcast by Lux Capital. We're closer to 2030 than 2020. More than half of humanity voted in an election this year. The IPO markets remain Arctic, and hordes of tourists are once again blocking all access to a New York City subway station. In other words, it's time for our final episode of the year where we recap the best singular moments across, count them, 68 episodes in 2024. Since it's me, we're going to skew toward the Riskgaming side of the house today. We'll have more to announce with Sam Arbesman and The Orthogonal Bet in 2025, but we've got 11 clips lined up for you. So let's get started, and we start with my close friend and my three-martini DC Power Lunch partner, Scott Bade, at Eurasia Group on AI deepfakes in elections.

Let's wrap up. We're in mid-June as we're recording this. It's been election high season of epic proportions this year. India, the EU, this year, I believe a majority of people around the world are voting. We will see if Japan might vote later this year. Certainly they are in Tokyo, but the two major elections going on outside the United States are obviously France and the UK, both of which were massive surprises. It came out of nowhere. We didn't expect. The UK was sort of time limited to late December, early January, so it's just a little bit early. In the case of France, it's a complete shock no one was sort of expecting. Obviously there's a ton of going on, and by the time we publish this, everything will have changed. But I'm curious, just with the technology focus, if you're seeing, this was supposedly the year of the deepfake. This was the year that all the AI technologies would destroy democracy, and it seems like democracy is actually doing okay compared to the worst sort of apocalyptic visions that we heard from the beginning of the year.

Scott Bade:

So as you say, it's the year of elections, and we've had a number of big ones that are in Indonesia and India and Mexico, Taiwan. And what's interesting is a lot of these elections were actually quite predictable in terms of, they weren't big change elections. Maybe slightly unpredictable results at the end, but Mexico, everyone knew that Claudia Sheinbaum was going to win, and she did very handsomely. And so there wasn't necessarily going to be much disinformation or AI infiltration there.

I'll give you a couple of examples. We were talking about UK and France. Taiwan has historically been a big focus of disinformation because the Chinese are constantly trying to influence Taiwanese politics and Taiwanese culture, et cetera, and the conversation. But in a way, it's worked against them because the Taiwanese noticed the last couple elections, and so they've really grown resilient to this. I was in Taiwan last year and meeting with civil society folks and government officials, and they started a whole digital ministry, which in large part is trying to counter the Chinese cyber and disinformation threat. They've created a lot of mechanisms. They actually use AI. They have a chatbot that you can feed in to say, "I heard this thing. Is this real?" And it'll kind of give you a Snopes and say, "Oh no, this is Chinese disinformation."

And so Taiwan's actually been pretty resilient, and not that the Chinese didn't try. And certainly there are narratives, and the KMT still won the parliament and parliamentary election. That's a more, not pro-Beijing, but more Beijing White party. Did that play a role? Maybe on the margins. Probably not too much. The DPP, the incumbent DPP still won. Their candidate won.

India, there's not really much foreign interference there. Actually, the use of AI was by the candidates themselves. So you saw this in Pakistan, you saw this in India, actually in South America too, where you've had candidates and political parties actually using deepfakes of themselves. Or in the case of India, you had one case I read that you had this candidate whose dad was a deceased politician and used a deepfake of his dead father to endorse him.

Danny Crichton:

That feels very Star Wars.

Scott Bade:

It was very Star Wars.

Danny Crichton:

Dress up my father. You could show up Obi-Wan Kenobi. Yes.

Scott Bade:

So that's a weird use of it, but again, probably if it had any impact, it's probably on the margins.

Danny Crichton:

Sorry, I'm going to get distracted, but I just have this image of bringing out the canon of the top politicians. Like the RNC, you're going to have Abraham Lincoln speaking on stage. At the DNC, you'll have FDR speaking on stage. I mean, why not just bring everyone back with an LLM and a hologram?

Scott Bade:

I mean, basically, what, you have the Disneyland Hall of Presidents version of the campaign rally now. So yeah, I mean, this is where you are seeing some creative uses. But then we did see in New Hampshire, right before the New Hampshire Democratic primary, which was not really a competitive primary, but Joe Biden still wanted to win it. You had these robocalls go out that were in Biden's voice saying, "Oh, don't vote, you have no reason to vote." And this is where I'm actually a little optimistic, is that it got caught pretty quickly. It was pretty obvious as a robocall, it got in the press. I think it was kind of everywhere. I'm sure there were people who did not hear about this, but it was debunked pretty quickly. And then what happened was a number of states immediately started banning the use of deepfakes in election campaigns or in ads. The FCC came in and banned the use of robocalls in election campaigns. And so not that the issue is completely dealt with, but actually the policymaking apparatus worked pretty well there.

Danny Crichton:

What's interesting is we shot that show back in July, and now that we can rewind across all of 2024, all of our prognostications actually proved accurate. It was not just the early elections in 2024, but also all the later elections, including the US election, that nothing really happened on the AI deepfakes when it came to election security. At our launch event for our own scenario on this subject back in October, we had Senator Mark Warner, chair of the Senate Intelligence Committee, join us and play the game. And he emphasized the same thing, that despite all the fears and concerns about what AI might be able to do to the election this year, it really didn't pan out. There were very small examples, and otherwise we sort of moved on. And so we'll see what happens the next time. But as of now, AI deepfakes has not been a concern.

Let's pivot now to clip two with James Pethokoukis, the author of the Conservative Futurist, on Up Wing and Down Wing.

James Pethokoukis:

I think sort of the important way to think about where we're coming from isn't left or right, but up or down. Up meaning there are problems, but we can fix them if we apply human intelligence and technology. And there may be some differences on the exact formula here, but broadly, that is a direction we need to go. We want abundance. If you think that's true, then you're probably an Up Winger. You may also be a Democrat or a Republican. That sort of pro-technosolutionist belief makes an Up Winger, and you can find them on both sides of the aisle.

But then there's the Down Wingers, which are sort of the opposite, better safe than sorry. If we do come up with great new inventions, the only people will benefit are the people in Silicon Valley. And by the way, those new inventions will probably just really disrupt our society, and robots are going to kill us, take all our jobs, maybe the reverse order, I don't know. And they're worried that the environment, that gosh, maybe AI will work, but we can't give it enough clean energy, so we shouldn't have AI just like we shouldn't have nuclear. And again, both sides, you can find those people, what I call the Down Wingers. And if I sort of know your view about progress and problem solving, to me, that's really what I need to know. That's what I need to know where you're coming from. Maybe not just that, but that more than anything really is part of the thesis.

Danny Crichton:

I think economics is more scrambled today than ever before. We see Republicans and Democrats putting together bundles of economic policies that would be anathema to the families of policies that we saw in the 2000s, 2010s, the Washington Consensus neoliberalism. And so it's an extremely exciting time to think about new ways of categorization. Who is antitrust, who is national security, who is export controls, who is abundance and prosperity? The answer is open for debate, and that is really, really exciting.

So let's go to the Down Wing side of the Riskgaming podcast, we always seem to end up over here, by pivoting all the way around the world to Taiwan. And this clip is from Gerard DiPippo, a senior geo-economics analyst for Bloomberg Economics, talking about the future of Taiwan under Chinese threat.

What would the impact be of a Chinese invasion of Taiwan, which is being more gamed all across Washington DC these days? I think there's been at least two dozen different versions of scenarios of this. And in some estimates, people have claimed it's about a hundred billion dollars. Others have pointed to a trillion dollars worth of global GDP damage, and others have scaled up all the way to maybe 10 trillion or more. And I just thought that this range was incredible because I feel like we know a lot about the Taiwanese economy, how it's integrated into global value chains. And so to me, it seemed like an unbelievably wide range, and you had happened to write a big deep dive for Bloomberg on this subject and covered it. So I figured asking you, if China were to go into Taiwan, whether that's just an embargo or something more aggressive, what do you think the implications of that would be economically?

Gerard DiPippo:

So first, thank you for having me. Second, at Bloomberg Economics, we did some scenarios which we modeled on both, say, a blockade and a full-scale invasion of Taiwan. The first thing to say is that the assumptions matter a lot, right? And there's a whole range of scenarios from, let's say a soft quarantine, where there's some interdiction of shipping, but not that much economic impact, to a full-blown amphibious invasion with missile strikes and occupation of the island and maybe the US getting involved in a US-China war. So that's the extreme case. Well, the absolute extreme case would be a nuclear exchange, but let's just not go there. Our assumptions for modeling purposes, we took those into two blocks. So there's blockade, there's war.

So we'll start with war, which is just the scarier version. We are assuming that there's basically a year of substantial dislocation globally, sustained combat operations. We're assuming that the US is involved against China. We're also assuming that regional shipping is substantially disrupted because if you look at the Second Island Chain where Taiwan is, where US forces would've to flow through the range of Chinese missiles, et cetera, it's not just the Taiwan Strait. It's basically all of East Asia going into Southeast Asia that would be well within the combat zone, even really going out past Guam, theoretically even into Japan, et cetera. So we assume massive trade disruptions.

The other thing is we tried to estimate what would be the impact if the world did not have access to Taiwan semiconductors, in particular, if they lost access to the high-end chips that TSMC makes. This is what makes it super hard. There are these macro models where you can simulate something like an oil price shock or something. What we're talking about here is well beyond the scope of anything that's in historical data. And on top of that, what we're dealing with is something which we call a golden screw, meaning that these chips are something that, in terms of global value added, are not huge, but without them, there's a lot of things like electronics, like cars that you just cannot produce at all. A good example of this in the real world would be Fukushima. In 2011, it knocked out some auto parts, which on the face of it were not all that valuable, but global auto production was substantially disrupted for six months. So imagine that, but much more important and much more skewed towards technology.

Our estimates are based on talking to people in industry, talking to people at Bloomberg Intelligence, which is a parallel organization in Bloomberg that specializes in specific markets or industries or firms. Basically, we tried to come up with the best estimate we could of how much the world could replace chips, and we ran it through our trade model. We also added in a financial shock model on top of that, and we used the chips basically to play with input output tables to simulate what it would do to the global production for things like autos and electronics. The scary number we got was $10 trillion.

Danny Crichton:

I don't think there's any subject more risk gamed or war gamed in Washington DC than a potential Chinese invasion of Taiwan, but almost all of them are about the military. It's about tactic strategies. It's about aircraft carriers and the Taiwan Strait. Very, very few of them actually look at supply chains, the economics, and global GDP impacts. And so when Gerard says that global GDP is going to decrease 10%, $10 trillion in an invasion scenario, first of all, it's believable. Second of all, it's nuanced, and these effects have very specific peculiarities based on which parts are coming from Taiwan, which ones can be substituted by other countries. And so it's really important that we get that right in scenarios and simulations.

But I want to turn to a more Up Wing example. And this time I've got Paul Collier, he's the co-director of the International Growth Center at the Oxford University and the recent author of Left Behind, talking about the future of development economics.

Paul Collier:

Understanding that downward spiral, what goes wrong. What went wrong in Detroit, what went wrong in Sheffield, they're hit by an adverse shock. Some industry closes. There are always adverse shocks that affect places. We can't fully protect against adverse shocks. What we can do is look at the consequences of adverse shocks and try and understand them.

And Milton Friedman thought the consequences of adverse shocks would heal themselves pretty fast. And he had a little image, which was an image of a harp with very taut strings. And you pluck the string, and it wobbles around for a bit, but it quite rapidly goes back to where it was. That was the image he used to explain why market forces would automatically remedy places. So Sheffield hit by a shock, Detroit hit by a shock. Property prices would fall, wages would fall a bit, and that would create opportunity, and so the market would move money in. Except it doesn't. What's going on?

So I've got a counter simple image, which is two sailing dinghies in a gusty wind. One is hit by a gust of wind, and the other isn't, and it topples over. It capsizes. And now, one dinghy stays the right way up. We know why. It wasn't hit by a gust of wind. The other dinghy is now upside down. Let's use some fancy language, hey. These are both locally stable equilibria, right? I don't know if you've ever sailed a dinghy, but most of the time you spend learning how to sail a dinghy is what happens when a dinghy capsizes because it's very locally stable when it's upside down.

So this crew haven't been trained in how to flip it back up again. So there's one dinghy that's upside down in the water, drifting backwards with the current, and the other dinghy is just sailing merrily along. You are going to play the role of market forces. You are now, and it won't be hard for you to imagine, there you are in New York. You are a fund manager in New York, and you've got to decide where to put your pensioners' money. You can put it in the upside-down dinghy that Milton Friedman believes will zip back up again, or you can put it in the right-way-up dinghy. What are you going to do?

Danny Crichton:

Yes, exactly. What are you going to do? And Paul, in his book, really emphasizes the importance of radical learning. This idea that, if you're a region, a company who is very behind, if you're in the dinghy that's sort of flipped upside down, the only way to catch up is you've got to get the dinghy back turned around, and it's got to be the correct direction. You've got to get the wind and the sails, and you've got to get moving as quickly as possible. And you can only do that by rapidly catching up, by working extremely hard. And we've seen this all around the world in global history, whether it's the Asian Tigers in the sixties, seventies and eighties, today, India and a couple other countries like Indonesia and Brazil. But at its heart is this concept of risk and the concept of chance and who is willing to put a risk and chance on this for a better return.

And that leads into my next clip, clip number five, with Kelly Clancy. She was the author of a great book on the history of games, chance, probability, dice that I really, really enjoyed. So let's talk to her next.

You also have this through line of dopamine, at least in the early chapters. What I thought was really interesting is not just in chance and surprise, but how important that sort of surprises both to playing a game, but also to learning.

Kelly Clancy:

So dopamine is a neurotransmitter. Often it's considered something like a pleasure molecule, but really it's a learning signal and a kind of motivation signal. Your brain is basically trying to predict the world. It's a prediction engine. And anything in the world that is operating at chance that you don't have a sort of model of becomes really interesting and intriguing to the brain. It wants to figure it out. And sometimes that unpredictability is because you just haven't formed the right model of that system, and sometimes there's intrinsic chance in the system, and you'll never figure it out. But the brain can't really distinguish between those, and so the unpredictability, the surprise of a chance element, can draw people in. It can become highly addictive. So that's why we see gambling addiction and people going to slot machines, and it turns out that 50% odds is the maximally addictive level of chance.

Danny Crichton:

So apparently the most exciting thing you can do over the holidays is a coin flip at 50/50. But I think when you combine Paul's ideas around radical learning with Kelly's ideas of dopamine, the learning cycle, and how that plays a role in risk and chance, you start to get a sense of how regions develop, how people invest in the future, how an entire country or even a company can start to think like, "Hey, where can we be in 10 years? What risk can we take?" And you get that dopamine effect going, and suddenly you are building something amazing.

But let's go to my next guest because I always get a dopamine hit when Zach Dorfman publishes something on the web. He's one of the best intelligence and skullduggery reporters out there based in the Bay Area, getting a lot of unique stories around Silicon Valley and espionage. He has a great story out in Politico Magazine earlier this year. We talked to him live about the 1980s and the Soviet Union.

Zach Dorfman:

I met a group of folks who were long-time FBI counterintelligence agents who had spent sometimes their entire careers essentially in San Francisco and Silicon Valley. One of those FBI agents, by the name of Rick Smith, became somebody that I-

Danny Crichton:

Is that his real name?

Zach Dorfman:

That is his real name. Rick Smith is his real name. He's a great guy. He still lives in the Bay Area. He still lives in San Francisco. He spent decades chasing Soviet and then Russian spies around San Francisco. He had this amazing story to tell, and this story was that basically in the early 1980s, he ran a massive sabotage campaign, where he personally recruited a Silicon Valley entrepreneur who was an Austrian but lived in the valley to run this high-tech sabotage operation where this Austrian, this entrepreneur would sell microchips and other microchip production equipment to the Soviet Bloc. But a great deal of it would be tampered with. It ran for years. They ended up selling millions of dollars worth of tampered high-tech to the Soviets.

What this operation that Rick Smith ran did was it didn't just sell them computer chips that had been tampered with, it actually sold them highly specialized computer production equipment that they were trying to purchase surreptitiously in order to open up their own computer factories. If you are subtly altering chip production technology, there's the short-term ramifications of it, which is that some chips didn't work. The chips they imported didn't work. But when you're talking about it a few levels up, basically you are kneecapping entire industries way, way, way upstream. And in theory, that's what entering was trying to do. And as far as I know, I'm not an expert on this, but I don't think the Russians really ever succeeded in an indigenous chip industry of the sort that you have in the United States.

Danny Crichton:

No, up until the present day, right? There's not a very deep industry there, and it is interesting because I mean, if you had an iPhone. You could turn it on and see that it's working, not working, or whatever the case may be. There's a lot of devices that work like this. In the chip industry, you get this tool, and you have to use it. It's a very precise tool. And the way you described it was, if you move just a couple microns off, is that just a miscalibration that you're doing? These tools require very excellently trained workers to operate them. So is it just, "Look, we haven't had the tool before. We have the tool, but is it our training that's off? Is it the electricity in the building?" All these different factors. So the possible deniability of it not functioning is, in my view, very to this high-precision industry that doesn't apply to a lot of other technologies that might've been also influenced by an FBI, CIA operation.

Zach Dorfman:

One of the most interesting parts of this story and reporting it out and speaking to FBI agents about it was asking them these sorts of questions, which was like, "Okay, well, if you're sabotaging the technology, they're going to know right away. How do you keep an operation going? What are the trade-offs that you have to deal with when you are running this?" It's technically called an offensive counterintelligence scheme. Because if everything doesn't work, obviously they're going to know that something's wrong immediately. But if you let too much unadulterated technology through, then is it possible that on balance you're actually providing a net benefit to your adversary?

Danny Crichton:

But then there's a wider question around the ethics of this, which was you didn't know where the chips were going. And so it was assumed it was going into a weapons system or a missile or into the Soviet Army, but it could go into hospitals, it could go to a lot of other places. But I thought it was interesting that there was quite a lot of discussion around those sorts of ethical issues. At the dawn of the computer sciences, we're starting to think about where all this technology is ending up all across society.

Zach Dorfman:

So yeah, I think there's two points, and I'll address the latter one first. I think it was interesting to me as I think it was, I'm glad you brought it up, but when I raised that question to the former FBI agents who worked the case, it was interesting to hear that they had really thought about this and that this was something that they were quite worried about. They admitted to me, we didn't know 100% where this stuff went. Once that stuff goes behind the Iron Curtain, we assume we know what their uses might be because we understand what their intelligence requirements are from things like the Farewell Dossier and other things, but they didn't know for certain. But they eventually concluded that they were just buying that stuff to take it apart and reverse engineer it, but of course that's a danger. I mean, you could absolutely imagine a scenario where some of this stuff does get rerouted for civilian uses, and then you are being put in a position of a real moral hazard.

Danny Crichton:

What I love about historical stories like Zack's is that it is really hard to know what's going on in modern intelligence operations. It doesn't leak really quickly. People haven't retired, people are still in the Clandestine Service, et cetera. And so you can go back to the 1980s and actually learn a lot about the techniques, the tactics of how Russia and the US and other world powers were sort of doing intelligence. And what's fascinating is there's an immense amount of continuity, we actually had another episode this year on the subject, and it doesn't change. The same tactics, the same strategies are taught in those tradecraft schools. And so intelligence agencies tend to do the same thing they've done for years and years and years, and so there's a lot of lessons learned from the past that can be applied to the future.

And that leads directly to my next guest. So Nick Reese, the inaugural director of emerging technology policy at the Department of Homeland Security, he came on the show to talk about the pager intelligence operation in Israel that knocked out most of Hezbollah in quite possibly one of the most amazing sabotage campaigns of all time. Here's him talking about that operation and what we can learn more about it.

And when you think about the sophistication here, these are not devices that are made in Israel. They're made overseas by multiple companies. The components of those presumably is probably not vertically integrated, but part of the normal global supply chain. How do you sort of begin to unravel that supply chain knowing that, I mean, you had to know that Hezbollah is going to buy these devices? And so there's a very limited window of time when you sort of have the intelligence that they are going to make a purchase to the time when you're able to intercept the shipment and actually do something to these devices to make the kinetic effect happen.

Nick Reese:

That would have to start at the realization that they are moving from phones to pagers, so that piece of collection is the most important one to have first. And so once that is done, there's going to be an internal calculation that says, "Okay, we can't get very much on collection anymore. So what can we do in response?" In this case, the decision was undertaken that we would intercept the supply chain and we would create some kind of effect.

So in order to do that, you would have to have sources on the ground, penetrations of Hezbollah, who could tell you, "These are the beepers or these are the pages that we buy, and we buy them from these three retailers." That would be the first step in the supply chain is to kind of understand that retailer. What is that point of sale where they're buying them? And then you sort of work backwards. And so then it's, okay, well, what is the fulfillment to that retailer? Okay, what is the transportation to that fulfillment center? And then you keep walking back.

In this case, it would be pretty hard to imagine that the manufacturer was involved here because of what will already be an impact to their business. You have to imagine that they got access at the transportation, wholesaler, or retailer. What you would do at that point is, once you've identified that, you would pay someone off, in effect. You would create a relationship, pay someone off to give you access, and then from there, this is where the complexity really comes in.

So identifying the supply chain, that part isn't as hard, but the hard part is that you basically have to set up your own assembly line at this point. I mean, this is maybe a little dramatized, but you can imagine somebody in the back room of the warehouse, so to speak, who opens the boxes, opens the enclosure, implants the implant, closes everything back up, puts it back in the box, has a shrink wrap machine to put the plastic back on the box, All of that stuff, and then it goes on the back of the truck and it goes to the retailer. But even before that, you have to invent the technology that goes in there. So the explosive, the charge that can be detonated remotely, that all has to be invented and then produced at scale and then integrated into these beepers.

Danny Crichton:

And it's a lot. And when I think about not only all the different steps, but the speed at which you had to do this because presumably this didn't take five years. I hate to say Hezbollah's a little bit faster than the Pentagon, but probably in terms of procurement is able to procure its phones a little bit faster than a traditional defense or homeland security appropriation. And so when you're able to do that, I mean, my guess is the window of opportunity was maybe weeks, maybe a couple of months.

So to me, it's like one aspect is, were they just lucky? They said, "Of the five things maybe on the market they'd go to, it's likely to be this one." Do they do all the above? And how did they sort of build enough of an infrastructure to say, "Hey, we're going to have an order for 4,000 of these devices," or whatever the number was total. How do we get enough people to where we have to assemble these? Because you mentioned as one example, you could have intercepted the retail, but the retail would've been in Lebanon. And Israel probably cannot have an assembly line of multiple people opening and resealing up thousands of devices without being sort of discovered in a reasonable basis. And so to me, that window of opportunity is what makes this so complex. If you had five years and you could have all the time in the world and you had a bunch of intel, it's all that plus concentrating that in a very specific period of time.

Nick Reese:

So my guess here is that this was a multi-year operation just because that's the amount of time that it takes to be able to do this. So I would be less inclined to believe that it was kind of a bulk order versus they probably were filtering these things in for a while, and they had intel that these were being used. And so they did some work up front, and there might have been a little bit of luck involved. I mean, truthfully, it might have been, "We're going to target their non-smartphone technologies. We're going to build this in." But in order to do that, the opportunity also has to be right in that, if you were going to open up a smartphone enclosure, there's not a lot of room to add additional gear and certainly not additional explosives that would cause any level of injury inside a smartphone enclosure, but there is in a pager or a walkie-talkie. You created the technology, you've identified the opportunity.

And so I would guess that all of that together had to have taken probably something on the order of two to three years. And the question that I think is interesting that I'm really following the news to try and understand better is why they decided to use it now because this is a one-shot thing. And once you use it, you're never going to be able to do this again or something similar to it. So why they decided to use it now is the part that I think is really interesting as well.

Danny Crichton:

We talk all the time in Silicon Valley about how it's not the idea, it's the execution. And I can come up with no greater example of that than the pager situation. As Nick just described, what an unbelievably complicated operation, the level of detail, the supply chains, all the factors that'd go into this. But the most important factor was patience, the patience to actually execute it and then to wait and to take advantage of the best possible moment for this operation. An incredible story and one that is definitely one of the highlights of 2024.

But let's pivot. We're sticking around in the intelligence community, which was not sort of intentional, but this is the order of operations on this show. My next guest was Randal Phillips. This is clip number eight. He was the head of China operations for the CIA for many years, talking about the future of the CCP, Xi Jinping, and the Chinese leadership.

One of the interesting dynamics with Xi Jinping's rise to power, and he was the one at Yahoo News who broke this news about the role of the CIA's network in China of its contestant network, and that happened roughly contemporaneously when Xi comes to power. Xi was a VP for multiple years, takes over as chairman of the CCP, and then becomes president a year later. And this sort of has this background of, there are spies lurking around all over the universe, and there's a lot more espionage going on here than you realize. I've always had the argument, and I pose this to him of, imagine you have become president, and you look around, and you're like, "Who do I trust?"

And I've always had this suspect that we've always been very surprised if you read the foreign policy blob of DC of, who was Xi? Why did he change so much? We knew him as VP, he was number two. He comes to power. He has a radical shift in government. And I've always said, look, this sort of moment in time was actually quite crucial to his sort of maturation into leadership. I'm just curious if you had any thoughts either about that sort of rise to power or that sort of shift because we went from that engagement, I'm thinking, oh wait, the Olympics that happened in Beijing, people were very excited at the end of the Jintao administration, into what is now a very competitive strategic competition between the two countries that didn't exist before.

Randal Phillips:

Well, actually I've got some very personal insights into that just given my last 12 years at the agency. I was chief of China operations, and then my last job ran East Asia division and then was chief of station in Beijing through summer of 2011. So obviously can't talk about it, but suffice it to say that Xi had some things to worry about because there were some successes there. And so the unraveling of that happened roughly about my last six months or so. I started realizing there were some things that we got to figure out what's going on, and then I and others worked that out to see what the scope of the problem is.

So I can absolutely see where Xi Jinping is watching this, and he's still a VP and all, but by that point he's the anointed one in 2010, 2011. And frankly, I think in a way it helped him in his domestic battle to ensure that he got the top job in fighting against Bo Xilai and others in that 2011, 2012 period. But it certainly had to be eye-opening for him, and he certainly has utilized that to fight back, not only in trying to go after that, but on empowering the ministry of state security and ministry of public security to say, "Hey, we've got to really up our game in terms of our counterespionage and counterintelligence capabilities." And that's where you started seeing all the campaigns on, "Every foreigner is a potential spy of the students. Watch out for redheaded student over here who might be trying to steal your homework," or whatever it might be, and everything else has happened in between.

You sort of fast-forward that to today, he still is feeling that. I think if you look back, for example, over this last year of the campaign against the Strategic Rocket Forces and the two leaders that about a year ago were taken out and haven't been heard from since, for the first time ever, the Strategic Rocket Forces, which as you know is the most sensitive part of the PLA, has been receiving very significant funding because Xi Jinping has been trying to expand China's nuclear force, and that's the people who run it. So that organization as a whole has been receiving billions and billions.

Now, the one thing I know from my history in China is that when and billions are rolling around, there's going to be corruption. And so Xi Jinping saw before what happened at pretty senior levels in the military that people had turned out to be susceptible to foreign enticement for this. And the corruption issue was so dire, he's got to be sitting there looking at the Strategic Rocket Forces, his most sensitive element of the military, and saying, "Can I really trust these guys? Are they still on Team China? Now what's going on here?" The Ukraine War of course doesn't help that. And they look at the one thing that the Chinese had about the Russians, they seemed to believe very strongly that the Russian military was a lot better than it's shown itself to be in Ukraine. And certainly a number of their own systems have been either bought from or modeled on Russian systems. A lot of the tactics and training from Russia, there's got to be some doubts rolling around in his head, which to my way of thinking, is not a bad thing.

Danny Crichton:

Randal was talking about corruption in the People's Liberation Army back in 2012, but I mean, this is an issue that is perennial and is an open question. Just this week, the Pentagon released its annual statement on Chinese power and growth of its military forces, and corruption was one of the largest elements that remains ambiguous in terms of Chinese readiness, China's force projection because after we learned from Ukraine, just because you have all this equipment doesn't mean it was maintained, doesn't mean it was purchased properly, doesn't mean it is as high quality as you expect, and that radically can transform the outcomes of war.

But that is sort of the end of our intelligence section. We now pivot to November, the US election, and what happens next. And with this one, we did the Riskgaming crew. So I have Laurence Pevsner, Micchael Magnani, talking about what's coming next. Here's clip number nine.

Laurence Pevsner:

This election is another example of incumbents losing, right? The old world order, whether you're left or right, is being shaken up. This year of democracy that we've had has basically been a year of replacing the current leaders and current heads of state and current parties. And so this raises the question of, is the era of neoliberalism over? Are we done with a flatter world where people are trying to free trade or trying to create these massive agreements, lots of multilateral engagement? It does seem like we don't know what's going to happen next, but it does seem like it's potential that we lose that entire framework for thinking about the world.

Danny Crichton:

Right, because if you look at everything from Reagan onwards, there's been sort of one theme around the Washington Consensus, which is open borders, free trade. America has the best industry. We're coming out of the Soviet Union in '89 into the nineties. We are the dominant force economically, and so we just want all these borders to go away because we have exporting markets. We can continue to sell goods, services, products overseas.

And that worked for a very long period of time, and I think it's actually important. Everyone always hates neoliberalism, particularly if you're in the academy. And Micchael, you were just there, so hopefully... It comes up all the time, and there's nothing better than the number of papers that reference neoliberalism without defining it, which is one of my favorite parts of academia. Nonetheless, when I think of it, I think of it as bringing China to the World Trade Organization, maintaining rules base, international order, all these great phrases. And it worked. The country became very rich, and that has been a theme even since the 2008 financial crisis. We continue to do this.

But people are getting worried about deaths of despair, they're getting worried about fentanyl, they're getting worried about deindustrialization across the American Midwest and the heartland up Appalachia. And so there's these greater questions of, say, where does things get produced? It actually matters that those supply chains that used to funnel into, say, Detroit are now many cases in Canada. In some cases, they're in Mexico and going up through Texas up the highway. And so that is a real radical shift because we didn't care what it was before. We just wanted to make the money, and as long as it was made here, and particularly in New York City, NYC, and it was publicly traded, we don't care.

Laurence Pevsner:

I think this is a case where the policy is starting to catch up to the rhetoric. For a long time now, when Biden first came into office, he ran on this idea of a foreign policy for the middle class. That was the slogan, that was the framework. It's not clear exactly. I served in the Biden administration. It's not entirely clear what that meant, and I think there was a genuine conflict within the foreign policy community and within the Biden administration about what that actually looked like in practice. I think we're going to see that same debate play out within the Trump administration as well. Like we talked about, there are people on both sides of this. As that debate plays out in the US, I think we're going to see a, I say bipartisan not like left right agreeing, but it's not necessarily going to be along left right lines of what a possible new approach to foreign policy, a more mixed strategy on free trade, say, what that actually looks like in practice.

Micchael Magnani:

And I would say honestly, some of these seeds, we thought, "Oh, the first Trump administration might've been a blip, back to neoliberalism with Biden." But sure, the facade changed. The Biden administration was a lot better at talking to our allies publicly, but privately we were putting up trade barriers. There was a big foreign policy for the middle class that had a lot of industrial policy, so the seeds that were planted in the Trump administration kind of stuck in the ground there, for lack of a better term, in the Biden administration. So I would personally argue that the era of neoliberalism is most assuredly over now because now you have the behind-the-scenes stuff, the industrial policy, the trade wars. That's been planted for eight years now, and now you're back to the rhetoric that's not so happy-go-lucky with our allies and partners.

Danny Crichton:

The 2024 US election was not a realignment election. A lot of people didn't shift all over the place, but it did open the door to both Democrats and Republicans reconsidering a lot of their old nose trims. And as I said earlier, the Washington Consensus neoliberalism, all this is sort of changing for both parties across the board, all demographics. It's sort of up in the air. And so again, one of the most exciting times coming up in the next decade as we sort of figure out what gets filtered where, how do parties rebuild their policy bundles, and what happens next.

But to end this show, we have two more clips. The first one is on our AI election security and deepfakes Riskgaming scenario that we launched officially in October with launch events in New York and DC, here's me and Laurence Pevsner talking about some of the lessons learned we got from the more than a hundred people who played this game in both cities.

And I want to talk about a little bit of the design. So for those who have been following the Riskgaming podcast and newsletter for a long time, we launched our first scenario a couple of months ago called Hampton at the Cross-Roads, which focuses on a hurricane hitting the Hampton Roads region in Virginia with implications around climate change and national security. With DeepFaked and DeepSixed, we have a very different game here. It's a game with dozens of people playing different roles, trying to focus on AI election security. And in this game, we have 54 roles, so people are playing everyone from the intelligence agency directors to people who work at the White House, Department of Homeland Security, all the way into the private sector, so people working at telcos, social media companies, et cetera. And the goal here is to bring them together in the storyline into an intelligence fusion center, so a place where we're trying to connect dots with disparate pieces of information around election security. And Laurence, you've seen this played out a couple of times, but how does that interaction sort of work in the game?

Laurence Pevsner:

Yeah, I mean, it's actually a little bit chaotic. You have a whole room of people, tons of different roles. Everyone is running around trying to first understand their own role, understand what their information they have is, and then identify who else has similar matching information and how can they piece this big puzzle together. It almost feels a little bit like a murder mystery party, I would say.

Danny Crichton:

Yes, yes.

Laurence Pevsner:

There's a hint of that, but of course it's a little more serious. And there's also a lot more going on than in that scenario. Rather than just being one murder or something like that, there's a lot of different potential threats that they're trying to identify, a lot of different threads to put together. How did you come up with this game, Danny? Where did it come from? What was the inspiration? How did you end up writing about this particular topic?

Danny Crichton:

Yeah, I mean, about a year ago I was working with Miles Taylor and Evan Burfield, and they run The Future US, a think tank focused on emerging technologies. And either from a national security lens or from an economic development lens, what are the risks and rewards for those particular technologies? And one of Miles's major topics was election security, and so he had reached out to us. He's a friend of Lux. I think we've maybe even had him on the podcast maybe two years ago. He has been a long time friend, and so we started collaborating, and he was hosting basically a policy lab day for a bunch of secretaries of state, Senate candidates, DHS, CISA, a bunch of the major agencies. And it was like, look, how can we make something more interactive, something that actually connects the dots for folks beyond just a couple of demos and a big discussion panel, whatever?

And so that's where the genesis of the game is. But the goal here was really to highlight the public-private partnership problem, which is the government has a certain pieces of information. Obviously the private sector has an enormous amount of purview into elections, whether it's campaigns, advertising, influence, social media, messaging, narratives, whatever the case may be. And that doesn't mean they have to influence those elections. They're trying to stay out of it, quite frankly. But they do know if Russia is spending money on particular ad networks or Iran or North Korea or whatever the case may be. And so being able to connect the dots from the private sector into the public sector was a huge part of that discussion.

DeepFaked and DeepSixed was a lot of fun. We had Senator Mark Warner, as we mentioned earlier in the show, a bunch of folks from embassies and different government departments, and of course a bunch of tech entrepreneurs because it's Lux Capital, and that's also who shows up at a lot of our events. But while you're going to luxcapital.com/riskgaming, you'll realize we didn't just launch a second game in October, November, but we launched our third one, Powering Up. And with this one, we wanted to go not just from politics or the emerging technologies, but into an economic simulation. So this one looks at the Chinese EV market. It was designed by Ian Curtiss, a longtime hand in China and Beijing and Shanghai, who has now dedicated his life to building amazing simulations and board games. And he's been joining us on building this particular scenario. Here's us talking about Powering Up.

Ian Curtiss:

Northvolt is this incredible battery company that started about six years ago. Multiple executives from Tesla came over to help build it out, and as they got going, there was just a lot of hype. They got some $15 billion in investments from all sorts of governments and companies, including scions of industry, Goldman Sachs, and so forth. And then here we are now, they're bankrupt. What happened? They had such difficult headwinds in an uphill battle in a world that has already been taken over by Chinese battery makers.

Laurence Pevsner:

Part of what your game does is model how this happens in the US and in the EU. Literally as we were running the game, we got notifications on our phones that General Motors was doing a write-down of their China business by more than 5 billion, and most of that was because they were just losing so much money to China. They've lost $350 million in the region just in the first three quarters of this year. I think that part of what we model in the game, and what I've seen now that we've run it a bunch of times, is just how difficult it is for the US and for the EU and for automakers in both regions to actually compete with what China is offering in country.

Danny Crichton:

Well, and I think one of the most important things is also just how fast this has changed, and we emphasize this a lot when we host these games. But GM and SAIC, the Chinese automaker that they did a joint venture with I think almost two decades ago, have been enormously profitable. GM made tens of billions of dollars of profit in the Chinese market selling internal combustion engine vehicles. But then over the last three years, China has exponentially increased the number of EVs on the road, and all the top brands, minus Tesla and to some degree Volkswagen, are Chinese domesticated indigenous brands. And so you'll be seeing a company like GM who's just used to this flush profits coming in quarter after quarter almost for free. It's not free to build the stuff, but the IP is free. It's already been developed, so they're just redeploying it to another market that's very lucrative, and now those profits are just disappearing. And so you're GM, and you're saying, "Well, what do I do next? I want my $5 billion and $10 billion every year, and it just comes in like clockwork."

Laurence Pevsner:

Yeah, and I think one of the things I really learned from seeing the game is that there's no one single reason why this is the case. It's actually from a ton of different angles that China is able to get strategic advantages in different areas. So whether that's IP or whether it's the processing chain, at this point, China processes nearly 80% of the world's batteries and 80% of the critical minerals to make those batteries. I mean, that didn't always used to be the case, but that's just part of the equation for why China has leaped ahead.

Danny Crichton:

And I think one of the most important things with Riskgaming, I mean, this is a good example where it's like, look, it's not just this or that. It's actually an equation that includes so many different policies, so many different global macroeconomic factors, so many parts in the critical mineral supply chain, joint ventures policy. You have changes in tariffs that have happened because of elections that took place. All these factors coming together is something that you can't really model and you can't really predict, so you have to experience it, experience it multiple times. You get used to the idea of reacting to what's taking place and trying to prognosticate a little bit in the future without being able to predict it fully.

It's been a year of monumental events, total chaos in some ways. So much randomness, so many big events. It feels like a turning point in history. But nonetheless, we never know what's going to happen next. 2025 is just around the corner, and we're going to go on hiatus for a couple of weeks here. But when I think of the structure we're trying to do, the thesis of Riskgaming, I just keep coming back to the same kind of basic principle, which is, the world is extremely complicated. It's extremely complex. It's interdependent. Changes over in one country make massive changes in others. And unfortunately, if you don't have a lens that sort of explores those complexities, that tries to understand the nuances in the system, you have no chance of even understanding the present, let alone the future, let alone the past.

And so I leave you at the final comment, which is, dive in deep, take the holidays to read amazing books, to meet with family and friends, because we have no idea what's coming next in 2025. But it is closer to 2030 than it is to 2020, and this decade started with COVKD, and we have no idea where we're going next. And with that, that's our show. See you soon.

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