The following is a rough transcript which has not been revised by The Jim Rutt Show or Jessica Flack. Please check with us before using any quotations from this transcript. Thank you.
Jim: Today’s guest is Jessica Flack, resident professor at the Santa Fe Institute, where she’s the Director of the Collective Computations Group. A very cool quote on their website, “We work on how nature collectively computes solutions to problems and how these computations are refined in evolutionary and learning time. We explore these ideas at all levels of biological organization from societies of cells, to animal societies, to markets, to machine-human hybrid societies.” Yep, talking about us there. She’s also the co-editor in chief of the Collective Intelligence Journal, which have you guys actually launched that yet? Or getting close, right?
Jessica: We’re getting close.
Jim: Yeah. We’ll have a link to it. I just went and checked and I couldn’t find anything, so I assume they’re getting close to the launching, but haven’t quite yet. There’ll be a link, as always, on the episode page at .jimruttshow.com. So check it out, which I’m sure will be extremely interesting.
Jessica: We are accepting papers. The first issue should be published online in the next couple of months.
Jim: Cool.
Jim: This is Jessica’s fourth appearance on the show on various topics. My personal favorite. And one of my all time favorite episodes, is EP48. Title, Jessica Flack on Complex Systems Dynamics. Today, we’re going to talk about something that kind of falls into that realm, which we decided to call nth order effects from the war in Ukraine. So let’s start with what is n mean there in nth order effects.
Jessica: Let’s see. So I think it’s worth actually before we introduce nth order effects or second-order effects, backing up a little bit and going over some related concepts.
Jim: Have at it.
Jessica: So the first one that I think we should put on the table is just a very simple concept of outlier. So an outlier is just a data point that differs you can say somewhat significantly from other data points. And an outlier can be caused by measurement error or by having the wrong underlying distribution. So you think you have a normal distribution when you really actually have a heavy-tailed distribution, or when the distribution’s changed, or it can be the result of stochasticity of chance. And so a second-order effect…
Jessica: Well, before we get to second-order effect, there’s one more concept we should introduce and that’s the concept of black swan. And so a black swan is an event where the magnitude of the event is measured correctly. In other words, it’s not due to measurement error… And Jim, you jump in here if you have a different take on black swans… but is nonetheless outside our current expectations. Let me just go over that again. So black swan is an event where you’ve measured its magnitude correctly, but its size is outside our normal expectations or our current expectations. And black swan differs… It’s distinct from a white swan, which is common and expected. That’s kind of where the term comes from. And you can turn a black swan into a white swan if you realize, upon studying more carefully the event and the factors giving rise to it, that the probability of it occurring is actually within the expectations of the model that you’ve built.
Jim: Yeah. Like you’ve seen 50 white swans, haven’t seen any black ones. You make the assumption there are no black ones. Once you’ve seen a 1,000, you’ve seen a few and you realize they have a probability of one in 500. That would be a classic example.
Jessica: That’s right. In other words, you might have had, for example, the wrong underlying distribution or causal model for the events you’ve been observing. Now, I think it’s worth highlighting something. So, I said at the start of this that a black swan is event that’s sort of outside your current expectations, but where you’ve made no measurement error. But there’s a second kind of measurement error I just want to reemphasize, and that’s that you could have been assuming the wrong underlying distribution.
Jim: And that’s something we talk about on the show quite a bit, that many, many people who have some level of numeracy assume everything is Gaussian. When in reality, most social network phenomena are fat-tailed sort of approximately power laws. And here’s some of the most ridiculous things. One I point out all the time is that during the 2008 financial crisis, some CEO of some financial service company that melted down said, “I couldn’t be held accountable for that. That was a 16-sigma event.” And I go, “No, it wasn’t actually. A 16-sigma event wouldn’t have happened once in the history of the universe even assuming if every atom in the universe was a financial services company. And rather, you were bit in the ass by fat-tail distribution that had about one in a hundred per year distribution, you idiot.” Right? So this is something we talk about fairly frequently and it’s very important.
Jessica: Yeah. I think, and your point too that, so it’s very hard to show that a distribution with data is power law, unless you have a lot of data. So often we just say that it’s heavy-tailed and it just means that there are some observations out in the tail that are completely expected, but much larger than the other observations, the bulk of observations that you have.
Jim: Yeah. But there are a lot more of them you than you’d expect in the normal distribution.
Jessica: Absolutely.
Jim: No, that’s the thing. Yeah, this is in parallel. Yes, no, plus or minus, whatever. But it’s a lot fatter than Gaussian, that’s the takeaway. So you go from once in the universe, if you’re unlucky, to once every 100 years. And there’s an example of going from the Gaussian model to the fat-tailed way of looking at extreme social events.
Jessica: And then, of course, the other issue here is that the world isn’t stationary. And distributions change, especially with feedback. And so a lot of times, we’re making assessments of outliers and we haven’t realized that the underlying distribution isn’t the same any longer.
Jim: Yeah. Another way to say that, closely related, is that we’re all strategic actors. And this happens all the time, people try to extrapolate assuming that there is no agentful reaction, right? So in reality, of course, all the human players are agentful, agentic in one way or the other. And so we’re in essentially a very, very complex game theory problem, we start to think about how does anything propagate out over this web of dependencies?
Jessica: Exactly.
Jessica: And now to come to second-order effects, the way I think about second-order effects is just it’s an effect that depends on something else happening first. So it’s kind of the result of joint probability distribution, but it’s important not to confuse a second-order effect with a longer term first-order effect. I think this is a common mistake. We think that if something occurs in the future, that is necessarily downstream. But that might not be the case. Sometimes second-order effects occur down the road, I think maybe often. But they can also be almost simultaneous with first-order effects. That’s just a little important note.
Jim: Yeah, let’s ground that with an example. What would you call the surge in price of wheat right after the start of the war?
Jessica: I would call that a second-order effect.
Jim: I would too. So we’re on the same page that it was a consequence of rather than an evolution of.
Jessica: Yes. And one that can be predicted in the case of Ukraine, which is a large producer of wheat. Everyone knew that in advance. Now, in terms of predictability, like the Ukraine example, second-order effects are often predictable even though they require first-order effects to happen first. And that’s just a consequence of there being strong causal relationships between the first and the second-order effects. So if a first-order effect is likely and its connection to a second-order effect is strong, then the second-order effect like wheat, that should be predictable.
Jim: And then there’s interesting… Predictable if you are focused on all the information. So we know that Ukraine is a big exporter of wheat. We also know Russia’s a big exporter of wheat. What most people don’t know is that Russia and Belarus, between them, are by far the largest exporters of fertilizer. And the war did not actually cut off their export capacity because they didn’t use the Ukrainian ports to any significant degree for their exports. But the economic sanctions, which one might call a second-order effect, produced the third-order effect of restricting the export, particularly Belarusian fertilizers. And they happen to be the producers, not just the export, the producers of 40% of the potassium fertilizer in the world come from actually Russia and Belarus. And so there’s where you have a cascade, a first-order, the war. Then we have a second-order effect, economic sanctions, predictable. But then you go, “Ah, whoever thought…” Somebody. Somebody at the World Bank probably knew this that when you put sanctions on Belarus and Russia, you’re cutting off 40% of the world’s potassium fertilizer.
Jessica: So tell me, Jim, since I think you know more about this than do, what’s the interaction between the cutoff of the potassium-based fertilizer and the cutoff of wheat, the joint consequence of that?
Jim: Yeah, it’s interesting. I did some research yesterday in preparation for this, just so I wouldn’t completely be making it up on the fly. And this is where you get into sort of deeper thinking about markets and things like reflexivity, et cetera, which is that most of the agricultural countries of the world actually already had their fertilizer stockpiled. But two of them are just about… Two of the big, less developed countries, Brazil and India, are about to go into their planting season. In India, the main planting season’s in June, right after the monsoon. And in Brazil, because they’re obviously Southern hemisphere, so opposite of us. Their planting season, the equivalent of spring planting in the U.S. is September, October. And it’s thought that India has enough. It’s also thought that Brazil does not. And the big crop that Brazil has in the world market… Well, they have a lot. They’ve become multi-facet. But soybeans in particular, Brazil I believe now the biggest producer of soybeans. And soybeans are very consumptive of fertilizer. So we may see soybean prices go up if… If, if, if.
Jim: How much does Brazil actually have in stock? We don’t know how much does India actually have in stock? We’re not sur. But what we do know is if this reduction of export were to continue one more year, there would be a lot of people in the world to hurt, including Brazil and India.
Jessica: Which countries can increase their wheat production?
Jim: India. And India has actually gotten a windfall so far, because they’re not actually quite substantial wheat exporter. U.S. certainly can. We can substitute… In fact, I’ve noticed a lot more wheat growing in the Shenandoah Valley here this year. I don’t think it had to do with Ukraine situation because it had to have been planted before it happened. I think it had to do with relative price between corn and wheat. And so in the U.S., you can generally substitute wheat and corn. And the price of wheat is up about 45% and the price of corn’s up about 25%. And so, at the margin at least, that will get a fair number of American farmers next year to plant more wheat.
Jim: Of course, farmers are always bitten in the ass by the fact that they all act together and plant lots more wheat, the price might actually go down. So they have to think through whether they want to play the first-order strategy, or think through and go to the second-order strategy, which says, “Everyone else is going to plant wheat, so therefore I’m going to plant corn.” And people will have mixes of those strategies. And some of them, the really smart farmers will explicitly take a mixed strategy, which will say volatility’s going to be high. And as we know about complex systems, predicting the future, it’s God damn hard. So rather than trying to make a play in one direction or another, instead of doing all corn or all wheat, I’ll do half and half. In which case, I’m self-hedged with respect to their relative prices.
Jessica: Yeah, excellent. That’s an important concept.
Jessica: Let’s return for second to black swans, because there’s one more point I want to make about relation to second-order effects.
Jim: Okay.
Jessica: And I’ll just put back on the table two concepts that you mentioned. One is agency, individual agency and strategy. And the second is reflexivity of George Soros. So one issue that I find particularly interesting about black swans, and coming back to the agency point, black swans can be genuine or they can be perceived. So we might perceive an event as extreme. Maybe it isn’t really, but because we have agency perceiving it as extreme can change our behavior. That’s important to keep in mind. So, one of the things about black swans that I find interesting is this, they’re consequences. So as events are perceived to be extreme, they tend to fundamentally… Fundamentally is important here… change the behavior of actors. So we see actors adopting different strategies when the stock market starts to crash than when it’s operating under sort of a normal volatility.
Jessica: And what happens as a consequence of a fundamental shift in strategy is that the underlying distribution can change. And when the underlying distribution can change, that means that second-order effects that might have been really rare under the previous distribution can become more common. So we get, with black swans and the feedback they induce, a potential amplification of hard to predict second-order effects.
Jim: Yeah. One reason that one would expect that is if it’s literally a black swan, i.e. nobody expected it. It’s not built into anybody’s strategy. And once it now becomes known that X is possible, well, one, you have to deal with the first and second-order effects of that black swan. But then you also have to deal with the strategic implications of the fact that this is probably going to happen again. And so both aspects will end up causing the fabric of all these myriad interrelationships to shift around in dynamic and agentic ways. And then you got on top of it, reflexivity, which for those who don’t know about the term, George Soros is the one that’s popularized it. It was around before him. But a shorthand version of it that doesn’t do full justice to it is that financial markets, particularly very volatile ones like currencies and commodities, are about the anticipation, of anticipation, of anticipation, of anticipation, right? And so et cetera, out for an infinite series in theory. Though, usually, three or four levels gets most of the meaningful information.
Jim: So, something that would happen at the first-order calculation in two years maybe, people may start moving in the market tomorrow afternoon in anticipation that, that’s going to happen. And then a second-order of traders will say they anticipate that people will do that. So they’re anticipating the anticipation. And then the parasites operating on traders, anticipate the anticipation. And so at least in my terminology, there’s an example of reflexivity in operation in human systems.
Jessica: And we discussed that on a previous podcast I think with Melanie Mitchell with respect to COVID when we were talking about the failure of models to predict the number of deaths, some number of weeks or months down the road. And one of the reasons for those failures in addition to the models being preliminary is that there were social interventions and other kinds of interventions that changed the COVID dynamics. And those have to be taken into account, like you’re saying, in this anticipation mode in our models, but it’s hard to do that early on. And that brings me to another point, which is coming back to outliers and black swans, it’s much harder to make predictions of events that are expected to have low probability if you have a good underlying mechanistic model. And one of the places where we see this sort of debate in a kind of fun way playing out is in the discussion around whether hot hands exist.
Jim: Ah, yes. The sports statistics debate, right?
Jessica: That’s exactly the point. This point is a statistical discussion. And that’s the problem. So you saw there’s originally this Tversky paper that was published in the ’70s in which the concept of hot hand, they debunked it. And it was statistical analysis. And then Joshua… I’ll think of his last name in a second… He and his collaborator wrote papers over the last couple of years in which they showed that in Tversky paper, they had the wrong statistical null model. And that with the right null model, you could show in some data that there was statistical evidence for hot hand. And Sid Redner, Santa Fe’s statistical physicist, has often also debunked the idea that there’s a hot hand or interesting patterns in, say, basketball shot data, and showed that it’s largely random walk. But in all of these cases, what’s missing is an underlying mechanistic model.
Jim: Yeah, causal model. Yeah, there’s no causal model.
Jessica: Exactly. And so in the case of the hot hand, what we really want is a neurophysiological model that explains how an individual might enter the hot hand state and stay? And what factors would contribute to that individual staying in it? And that would help us know where to look in the statistical data for the start and end of the hot hand, which would make a much more refined null model than the ones we’re currently using.
Jim: Yeah. I’d point people towards Pearl and his work on causality and causal networks as at least a good introduction to how to think about the fact that causal models are perhaps more subtle than people sometimes think they are, and could indeed manifest in performance and baseball in such a way that it wouldn’t necessarily look like it’s there because of the model of causality could itself have a fair amount of stochasticity to it. Right?
Jessica: Absolutely. And it also is worth pointing out that the literature that linking mechanistic models to Pearl’s framework is still very much in development. So when I say a mechanistic model, it obviously is about causality, but the mapping to a causal network in the sort of Pearl sense is still under development.
Jim: Indeed, indeed. That’s interesting.
Jim: I’m going to react to what you said and throw something out as an example of a second order… an nth order… I don’t know if it’s second, third, fourth… about black swans. I hadn’t thought about it that way. I would suggest… At least I would hypothesize that most people, say, running countries in Europe thought that a World War I style war in Europe was between big ass armies hammering the shit out of each other was very unlikely to occur anytime soon. And the defense budgets reflected that. Now, with the fact, well, shit. World War I beat the out of each other. Wars are possible in Europe. We better raise the hell out of our defense budgets. And Germany may well double its defense budget.
Jim: And one could argue that, one… There’s two different ways look at that. One, it’s, sort of a specific counter to Putin. And the other is, it’s a reaction from the black swan appearing, which had been thought not to exist. And trying to disentangle those two is difficult. That strikes me as an example of this black swan that most people had discounted down to a very low level, suddenly there it is. And now we have to take it into consideration, and so we’re raising our defense budgets a bunch.
Jessica: Yeah. I think I have two remarks in response to that. The first is, I noticed in comments, in people interviewed in Ukraine, journalists and so forth, that there was this remark being repeatedly made like, “How could this be 2022 and we’re having this kind of traditional 20th century war”, as you said. And the implication there was that we now live in a civilized world. Or at least certain sections of the globe are civilized, which is problematic for a variety of reasons. But that was kind of the implication. So that’s a little bit different than the sort of colloquial wisdom that democracies don’t fight each other, which maybe has some empirical basis, but it’s a short history.
Jim: And Russia wasn’t a democracy anyway, right?
Jessica: Russia is not a democracy, right.
Jim: But they did have McDonald’s, so it was yet another refutation that no countries with McDonald’s had ever fought each other. And there’s only a few examples, but it is one.
Jessica: I think the more powerful explanation for this sort of nonchalance about the possibility of this kind of war happening is trade. And so there’s this constant return to this argument that because we are dependent on Russia or Germany in particular for energy resources, oil, and gas, and so forth, that there couldn’t be a war. But I think what people fail to do is look at the asymmetries in those trade arrangements. Now, obviously, there are economists who are looking at these kinds of things. But more mainstream understanding I think neglected those asymmetries. And so that needs to be examined more closely.
Jim: Yep.
Jim: And the other issue specifically about trade is people forgot history. All I have to do is go back and look, world trade grew very rapidly in the late 19th century and early 20th century and reached 25% of global GDP right before World War I. And many, many people thought large scale war amongst the industrial powers was impossible for that reason. Well, guess what? And here’s the interesting thing, 25% fell very rapidly. And global trade, as a percentage of GDP, did not reach 25% again until 1988.
Jessica: Right. Amazing.
Jim: Took 78 years. Now, it’s higher still. But they were completely wrong. And basically, we had a whole series of wars. Obviously, World War I, World War II, the Cold War, et cetera. And so just looking at that historical example proved that hypothesis is wrong.
Jessica: I don’t want to see the baby thrown out with the bathwater. So I think there’s some nuance here. And one is that, trade is necessary but not sufficient. That might be one part of this. And the second is the structure. The asymmetries in those trade networks matters possibly quite a bit. And in fact, not only matters in terms of preventing these kinds of conflicts, but could actually be used as leverage as we’re seeing happen in this one, in these kinds of conflicts if it’s distributed the wrong way, if there’s this imbalance as there is in the control of energy by Russia.
Jim: Yeah. Well, of course, there’s lots of interesting asymmetries in trade. One that works in Russia’s favor is on energy, but one that definitely does not work on in Russia’s favor is microchips.
Jessica: Good point.
Jim: Yeah. It turns out many of their military missiles require American-made, or Dutch-made, or Korean-made microchips. And they’re going to have a shitload of a hard time building more missiles and stuff. If this really does turn into a multiyear World War I style, knock down, drag out, they’re going to have a real problem replenishing their advanced munitions for things if they can’t get the state of the art microchips from somewhere in the West. And we take a long time to re-engineer those things to use Chinese chips, for example.
Jessica: Yeah. And that relates to another point, which is that this isn’t really a 20th century war. It’s really a hybrid war. It’s using conventional warfare plus a lot of cyber warfare that we don’t know so much about.
Jim: Yeah. In fact, friends of mine, John Robb, who’s been on this show quite a few times, often to talk about Ukraine war, he calls it fifth gen warfare where the cyber part is huge. And that’s actually been I think quite surprising to everybody how well the Ukrainians have done in the cyber war, in the memetic war. We had this idea that the Russians had this great ability to manipulate the West. But turned out, they haven’t done shit. Nobody much likes Putin, and they have got very little sympathy. And the Ukrainians have been brilliant in every aspect of PR. It’s really been quite remarkable, at least in the West. Now it is true that the Russians have had more influence in places like China and India.
Jessica: Actually, there are a few analyses I’ve seen come out on this topic yet. And I haven’t looked at them carefully, but they seem to suggest that most of the Russian energy in this respect is elsewhere. It’s not directed toward the West which, I guess, the Russian’s think battle already lost. And it looks like the energy that’s going into that propaganda movement in these other countries is pretty large. So it’s not something to, I mean, the sort of Ukrainian skillset may also be a Russian one. We’re just not really seeing it as the way we’re seeing the Ukrainian.
Jim: Yeah, that makes sense. And that’s a good point because they’re clearly putting a lot of work into certainly India and China, two biggest countries in the world. And have actually quite strong PR in their favor, majority in both countries. Though I think in India, it’s slipping a little bit. But in China, it’s certainly still a majority.
Jessica: Since we’re sort of on this topic, another point I think that is worth highlighting and it ame up a little bit earlier in our conversation is that we’ve actually had two major events back to back here. So we had a pandemic, and still have it, that generated social instability, supply chain chaos, workforce changes. And now stimulus packages that occurred at the beginning of the pandemic and during, that were designed to ameliorate some of the problems that I just listed are having liquidity and interest rate effects, right? And then this is followed by and coupled to this Ukraine war, which is a huge financial perturbation. And we can talk about what it means to be a huge perturbation, if that’s interesting.
Jessica: Financial network, potentially financial network realignment because of the sanctions. Food and energy shortages, which we’ve already discussed. An increased flow of arms around the globe possibly, which I haven’t seen many people talk about. But obviously, into Ukraine, and then the sort of correspondent geopolitical instability. So just these two huge perturbations back to back.
Jim: Yep. And then one of them I pulled out based on an email thread I think you were on, is the dollar is up quite a bit since the start of Ukraine… Often happens during world uncertainty. And I looked up the number and there’s 12.4 trillion of dollar denominated debt outside the U.S. And at the peak, the dollar was up about 9% versus a broad basket of our trading partner currency currently up. It’s currently about 6.5%. But even 6.5% is almost a trillion dollars of nominal wealth that has switched due to the dollar change as… call it dollar change, a second-order effect. And there’s been winners and losers. People who actually hold those bonds have gotten a windfall. So if you hold some, say, Brazilian bonds that were denominated in dollars and you live in Brazil, those bonds are worth probably more than 6% or 7% more for no good reason other than the Ukraine war.
Jim: On the other hand, when Brazil has to refinance those bonds, they’re going to have to pay… Assuming nothing else changes, which of course is wrong, but assuming nothing else changes… it’s going to cost them 6% more to fund their debt next time around due to relative changes in currency. And so that’s a second-order. Then a third order effect as these things play out all triggered from the second-order effect of the rush to the dollar during times of international crisis.
Jessica: Yeah, it’s worth pointing out. So one of the reasons I got interested in second-order effects goes back to this work on robustness I did in the 2000s and 2010s. And in that work, we were studying the consequences of a certain kind of conflict management actually in monkey groups or the sort of connectedness of monkey social networks. And we found there were certain individuals who were responsible for doing this policing. They broke up fights among other individuals. And we found, by removing those individuals, by disabling the policing mechanism, that the social networks of the other monkeys changed. So the policing mechanism was actually serving as a kind of modulator of how individuals interacted with each other. And this is an indirect or second-order effect that’s not observable when the policing sort of mechanism is working. It only becomes observable under this perturbation where it’s been removed.
Jessica: And so the basic point was that these monkeys had much richer, much more positive social networks when the policing mechanism was working and much impoverished networks when the policing mechanism wasn’t. But it was not possible to see the effect until the perturbation. So an interesting question is, what hidden effects. I mean, we can anticipate some of these and you could have probably anticipated in the monkey case if you understood how the cost function for social interactions relied on the policing mechanism. So what the policing mechanism was actually doing was making the cost of interaction with your group mates lower, because if you did get into a fight, there was somebody there to stop it. So you could maybe have predicted it would have this effect, but often these things are missed until the perturbation happens.
Jim: There’s a good example from Ukraine. I suppose you could have imagined it, but if you look at the history, it seemed somewhat unlikely that Finland and Sweden would join NATO, right? And those are two countries that have historically, particularly in the Swedish case, been a couple of 100 years, have been militantly neutral in the… I mean, people forget, Sweden was able to be neutral during World War II despite being surrounded by German military. And for them to have actually moved their flag from neutrality is a pretty big deal. And what affects that will have in the future? Not sure, but there’s an example of perturbation World War I in Europe causes Sweden and Finland. And of course, Finland, in some ways, is even more significant because it’s actually got a longer border with Russia… moves explicitly into NATO with all kinds of third, fourth, fifth, and sixth-order implications that it’s hard to see.
Jessica: Well, so the larger story there is that no one really, and maybe not specially Putin, predicted that the NATO Alliance would become stronger as a consequence of his actions. But one has to consider… So, we talked a lot about collective behavior and collective intelligence during COVID. And I even met with Melanie, who wrote an essay in which the beginning of the first paragraph, the essay is about the enormous potential to harness collective intelligence to produce good social outcomes, like the control of COVID. And in many ways we failed to do that, but somehow in the build up to Ukraine… it seems like from what I read… an incredibly strong behind-the-scenes alliance was built in Europe and with the United States in response to Putin. And I wonder to what extent that actually was facilitated. Was it facilitated by this collective intelligence failure with COVID?
Jim: Interesting. It might have been-
Jessica: Right. So we’re talking about this in a way that we weren’t…. this kind of coordination, collective intelligence in a way that we wouldn’t have been I think without COVID, so it’s on everyone’s minds.
Jim: That’s interesting. Yeah, that makes sense. Because there was a failure of coordination then. And hence, simple takeaway, better coordinate next time something bad happens. Very simple rule. And even politicians are capable of following simple rules, right?
Jessica: And even more than that, just the social and economic consequences of COVID made everyone feel a bit fragile. And so the stakes for responding correctly in the Ukraine case are higher perhaps than they might have been without COVID.
Jim: Makes sense.
Jim: Also, our financial situations are more fraught for instance, which actually in some ways makes the reaction even more impressive. Now, again, John Robb, who I mentioned previously, he has a theory that the coordination comes from another network, which we don’t generally see, which is public opinion. He believes that the stronger than expected reaction from the Western Europeans in particular is actually not driven by the masterful diplomacy of Biden, but rather from a genuine grassroots network uprising in disgust at Putin and the disgust at reintroducing gross 20th century style war into Europe. And that even ones that were probably reluctant, like the Germans, were stampeded by network public opinion, which could [inaudible 00:31:54] more or less instantly. And of course, being a fifth gen war with plenty of videos of horrific war crimes and just the general brutality of war. And so he would argue that’s what actually produced the seemingly coordinated behavior rather than any magical diplomacy by anybody.
Jessica: Yeah, I expect it was an interaction. And the reason I say that is David and I… David Krakauer, he’s a president of SFI, and also a collaborator of mine… just published a paper in PLOS ONE, which I will be probably writing about on Twitter in the next week or two, on institutional change and how it affects grassroots or bottom-up perceptions of laws, regulations, and social norms. So one of the motivations for writing this paper for me was a paper came out in PNAS a couple years ago on gay marriage. And it was observed that there was this flip. So, the paper Dave and I wrote is on sort of when do you get tipping points in institutions, critical points and so forth? What causes that? Why are some institutions changing slowly? Why do some flip? Why do some unexpectedly change fast?
Jessica: And like I said, the motivation for this paper in some part was this PNAS paper on gay marriage in which the authors observed that there was this flip in public perception, acceptance of gay marriage after federal legislation was passed. And when they looked at the data more carefully, they found that there was actually strong latent support for gay marriage in the population in the United States, but that everyone was afraid to express their opinion because they thought their neighbor had a different opinion.
Jim: Interesting.
Jessica: So once the federal legislation was passed, it was like this global signal of acceptance and everyone felt much freer to say what they really thought.
Jim: That’s very interesting. I could see that.
Jessica: So this is a kind of an example of what John Robb is saying. There is this kind of grassroots change or micro-scale level change, but it was latent and hidden because of perception. And then when there was federal legislation or an institutional norm in place, this time imposed from the top, the true perception was revealed. And so that might be a little of the case in Europe. And I don’t know what role Biden maybe played in that, just facilitating the expression of it. Those are ideas to explore. We definitely don’t know the answer yet. But I like this point that there was this kind of grassroots distaste for brutal conventional warfare, and that was part of the motivation.
Jessica: It brings me to the other sort of girl in the room, which is the nuclear element. And so, I think we’re in this interesting situation where we have this rudimentary game theory that everyone holds in their heads, every person has it sort of in their heads in the U.S. that you don’t go to nuclear war with another nuclear superpower. And we believe science tells us that is the right decision. And of course, there’s a lot of variation hidden in there, which there aren’t just two superpowers. There are three. And now there’s the opportunity or the option of using a nuclear weapon on a nation that’s not a superpower as punishment for another superpower’s action, or on a nation that doesn’t have nuclear capability. And so it’s quite complicated discussion and there’s no reason… I think this logic or principle that we carry around in our heads is very misleading.
Jim: Yeah. And people who do follow this do know that the Russians have a doctrine called escalate to de-escalate, that if things are going really badly, you can escalate to tactical nukes to make the other side back off.
Jessica: Exactly.
Jim: And it may happen in Ukraine. I think more likely we get sort of a frozen conflict situation there. But it is possible that the Russian sociopolitical system starts to crack the way the Germans did in 1918 or the way the Russians did in 1917. I don’t think the Ukrainians have the power to flat out beat the Russians, at least not anytime soon. Maybe over a period two or three years, but there could be a kind of a collective breakdown of the willingness to fight and some political turmoil all going on at the same time, which has a effect of the Russian military more or less collapsing. Under a scenario like that, the escalate to de-escalate could actually be what happens where either it’s a warning shot. One theory is the Russians would cite off a nuke over the Black Sea. Or heavier, they would take out a remote military base with a small tactical nuke. Or one step above that, they take out a isolated town of 50,000 people. But we have to be prepared for that because that is actually part of Russian doctrine.
Jessica: Yeah, it’s part of Russian doctrine. They could also use a small tactical nuke near Chernobyl and create a confusing situation that would make it hard to respond to.
Jim: They live to the east though, that’s not smart. I don’t think they’ll do that. That’s why I was not too worried about Chernobyl because the wind blows in their direction. So that would be exceedingly stupid for them to do.
Jessica: Well, there are other nuclear facilities in Ukraine. But that’s a good point, there are some constraints. But I do think Sweden and Finland joining NATO, or about to join NATO, this may be part of that discussion. I think during the Cold War, up to the fall of the Berlin Wall, we still very much had this sort of old game theory model in our head of super powers fighting each other, and weren’t thinking so much about these alternative uses of nuclear weapon as leverage. I like you say, over the Black Sea, or using a small tactical nuke, or just generating a confusing situation, a nuclear situation, that would make it hard to assign blame. And so these are new elements. And then the reaction too of China to the use of a nuclear weapon by Russia or any of the United States and its allies, that has to be factored as well. And so there’s so much more uncertainty.
Jim: It’s opened up a number of scenarios that were thought very low probability, have suddenly become much higher than near zero. Right?
Jessica: Exactly.
Jim: You’ve said, “What’s the chances of Russians using a tactical nuclear weapon in Europe?” If you’d asked that question two or three years ago, people would say, “Close to zero.” Now you’d have to say 10%, and that’s a much bigger number. We now have to actually add it into our calculations.
Jessica: Yeah. I think you could say that it was basically effectively zero last summer. And I do think, at the start of the Ukraine conflict, it seemed like the probability… This discussion, at least in social media and in the news, was much more heated. It’s come down a bit, but it seems to be building again.
Jim: Well, of course, the other thing is facts on the ground. I did a whole bunch of podcasts right after the war started with various experts, and they varied. One of them was actually the most prescient, which was, he said, “Nope, the Russians aren’t going to win this.” But the majority of them said, “It’ll be over in two weeks. Maybe another two months for the Russians to mop up and take all of Eastern Ukraine.” Well, that didn’t happen. Turned out the Russian military was a whole lot worse than anybody thought it was. And the Ukrainian military was better than most people thought it was. And the result is now that it is possible Russia could lose, or at least be in a really bad situation at some point. And that was not actually any expert’s opinion the first week of the war.
Jim: The first week of the war was arguing, “Is it going to be three days? Is it going to be two weeks? Is it going to be two months? Russian’s definitely going to win.” But since the events on the ground have shown that the perception of both sides was wrong by most experts, but not all, that escalate to de-escalate scenario, we could reach it. So again, as you gather information, as you probe the system, the probabilities have to change.
Jessica: Right. So now we have two potential perturbations on the table. One would be the consequences of Sweden and Finland joining NATO, Putin’s reaction to that. And another would be in terms of black swans. And another would be the second-order effects resulting from the detonation of a tactical nuclear weapon. Right?
Jim: Yeah. Well, actually another one is Ukraine beats Russia, or Russia is cracking under the stress. I mean, Ukraine’s not going to defeat Russia in a head-to-head slugging match, but it could be a 1918 situation where the German empire just lost the will to fight and had to sue for peace. And that’s what could lead to the nuclear… I don’t see anything short of that leading to the nuclear escalation, one would hope.
Jessica: But it is interesting that now either for reasons of corruption or a lack of appreciation of what’s actually needed, Putin failed to invest in his on-the-ground conventional warfare, but has invested in extensive nuclear arsenal.
Jim: Well, actually they did invest a shitload in their conventional military after they performed very poorly in the Georgian conflict, where they won but only by brute force. And they spent a tremendous amount, in theory, upgrading their conventional military, but nepotism and corruption appear to have sucked an awful lot out of that. And their doctrines are just not very good. It’s astounding to everybody that they have been unable to suppress the Ukrainian Air Force. They’ve been unable to suppress the Ukrainian air defenses. If the U.S. had been up against the Ukraine, there wouldn’t have been a single Ukrainian thing flying after about two days. But the Russians just seemingly can’t execute state of the art air war essentially.
Jessica: But so even the corruption explanation, which is a little different than just a plain out failure to invest in conventional warfare, suggests a kind of lazy attitude a little bit about the importance of conventional warfare. So I’m just wondering… I don’t know the answer to this… to what extent did Putin himself expect that most warfare, going forward, was going to be either using nuclear capability as leverage and/or cyber warfare, and didn’t really expect to have a protracted… perhaps because he overestimated the initial success… protracted on-the-ground conflict.
Jim: Yeah. It’s probably low probability slice of his scenario planning. Because, again, if you believe what you hear… And we have to remember we’re always being spun by the Ukrainians, right? They’re on our side, but they have every incentive to spin as anybody else does, so always have to take that into consideration. The theory that Putin thought Kiev would fall in three days, and that was his main bet. Doesn’t really matter how shitty your military is, the stresses aren’t going to show in three days or even in two weeks. But as it turned out, once you get past two weeks, then one of the more pressured people that I talked to did say that if the Russians don’t win in two weeks, they’re going to be in trouble because their logistical capabilities are so bad and their ability to do combined arms-land-air is so bad that, that’s going to surface and it’s going to bite him in the ass in a very severe way. He was exactly right, as it turned out.
Jessica: There’s this idea that actually David has worked on, an evolutionary theory called arena selection. And the idea of arena selection is that before you release the strategy to the world, or the organism releases the strategy to the world, or actually plays it against competitors, the organism test it out in a limited arena environment, a safe environment to see how well it works under stress. And this idea has been on my mind a lot lately. It’s a bit of a loose metaphor, but partly because obviously China is observing how the Russians are doing, the response of the West, Ukraine, how conventional warfare is working on the ground, and learning presumably a tremendous amount. And so this is a second-order effect.
Jim: Yep, indeed. And one that’s very interesting. And again, I’ve talked to some of my guests, every one of the guests I’ve had, that’s always been the last question. All right, what’s the impact of the lessons learned so far from Ukraine and China. Now one of my guests, I think he made a huge blunder. He said, “Well, the Chinese are going to attack Taiwan sooner.” And I said, “I’ll be you a bottle of my best bourbon against the bottle of your best Slivovitz”, because he’s a Slovenian. And I said that, “China’s going to learn the opposite lesson, which is, in the history of warfare, over a long centuries arc, there’s been changes in the relative efficacy of defense and offense.” In fact, the amazing slaughters in the U.S. Civil War came around from the fact that at West Point the generals were all trained on Yamane’s books about the Napoleonic conflict. And the balance of technologies in the Napoleonic era favored the attack. A bayonet charge will prevail two thirds, three quarters of the time under Napoleonic conditions.
Jim: The technological change was the rifled musket, which tripled the effective range of the musket. So it used to be, they couldn’t hit you until you’re within 75 yards, and really within 50 with the rifled musket and the mini ball that came in well after Napoleonic era. In the Civil War, you do pickets charge and your guys are starting to fall at 200 yards. And by the time they get to your line, most of them are dead. And so that one change in military technology resulted in the balance of statistical power going from the offense to the defense. And if you look very carefully at civil war battles, very, very seldom to decide that was on the tactical offense win. And some of the classic battles that Robert E. Lee won, Second Manassas and Chancellorsville in particular, were classic examples. What he did was he left the other side attack first, and once they had blunted their spear on his shield because of the superior power of defense, he then counter attacked while they were out of their defensive positions. And then caused them to panic and have to break and run for DC.
Jim: And since World War II, the general assumption has been that combined air-land armor, et cetera, gave the advantage to the offense. World War II, lines move very rapidly. But I think what people seem to have… even in the first Gulf war and the Iraq second war, man, we blew right through them. Things move very, very quickly. Well, it turns out that in more closely balanced forces, smart weapons may have moved the balance now back to the tactical defense. Who would’ve thumped that guys with javelins would stop the Russian army, the very tank heavy, very artillery heavy army? But it did. And if I were China, the lesson I would take is, “I don’t think I want to fuck with Taiwan anytime soon. I think I will wait for it to fall into my hands through politics and economics. That trying to attack it is probably more dangerous than I would’ve thought, before Ukraine.”
Jessica: But not just from the war point standpoint, also from the collective response of the West, which was unexpected. Right?
Jim: Yeah, I think that’s also good that if the West could respond about Ukraine, will the Pacific periphery respond very strongly against Taiwan, the Japanese, the Koreans?
Jessica: And the potential success of U.S. and Ukraine sharing of… So this unusual sharing of intelligence that we’ve been hearing about. And possibly, behind-the-scenes intelligence with respect to locations of Russian troops, messing with missile GPS, or what… I don’t know how missiles are actually with the navigation-
Jim: Most are GPS these days, but some of them aren’t. There’s various technologies.
Jessica: Right, because there’s been, I’ve seen in the press, a lot of discussion about surprising failure of Russian missiles to hit targets.
Jim: It could just be they’re shitty, right?
Jessica: But so anyway, I think China must be thinking about the cyber warfare angle here. And obviously, we know China’s excelling, and exploding, and it’s developing its AI capacity capabilities. So time is on their side.
Jim: Maybe. Though, like Russia, a lot of their investment is wasted due to nepotism and corruption. And so you probably have to divide by four in terms of actual muscle. So, they’re probably still well behind us in that category. Even though they’re putting more meat into it, their stuff is just so corrupt and particularly nepotistic that-
Jessica: Is that right?
Jessica: Well, they’re doing interesting experiments with social credit systems that use machine learning in AI where they’re doing different policy experiments around China that are, obviously, from the West point of view, unethical. But very, very interesting from the point of view of controlling formation of institutions, controlling individual behavior using microscopic data. It’s a very different strategy than Russia uses.
Jim: Russia’s too incompetent to pull that one off.
Jessica: But it also operates, I think, using older… It doesn’t appear to me… Russia’s control of the population doesn’t appear to be as micro-scale as-
Jim: Yeah. Well, it’s not. They’re totally incompetent when it comes to that stuff. They just use crude, very crude… You can still get through the Russian firewall without any problem, unlike the… It’s much, much more difficult to get through the Chinese firewall. And they don’t have anything like social credit systems, or constant surveillance, or anything like… They’re just a basic dictatorship.
Jessica: But that brings me to one of my final points, which is getting a glimpse in a way that I think was really only science fiction before the possibility of a bipolar war that’s divided up in a complicated way between democratic leaning nations and authoritarian/totalitarian ones, but where the potential diversity in the total totalitarian or authoritarian regimes is actually higher than one would expect. We’ve got lots of different models on the table now from the sort of social credit dominated China version to the very crude brute force Russian version.
Jim: That is true. That’s interesting.
Jim: And you got hybrids like Turkey and Hungary, which are kind of crackpot traditionalist. And we might have that in the United States here in 2024.
Jessica: Let’s hope not. But yes, we’ve certainly been at the cusp at times. So that possibility of this kind of bipolar world and strange alliances forming between authoritarian regimes is very interesting.
Jim: Yeah. One of my little pet ideas actually haven’t circulated, but I’ll put it out here for the first time, which is maybe it’s time to end the United Nations. And instead, start a new organization of open democracies. And if you want to be a member of this open democracy world governance, you have to agree to leave your internet open. Right? You have to agree to international supervision of your elections. You have to agree to reasonably strong, free speech. Maybe not quite as extreme as the U.S., but say as equivalent of say Canada or something like that, which is considerably less free speech than the U.S., but a lot more than any authoritarian country. And that those countries should just club together and operate collective security, because that was the original reason for the United Nations. No more World War II, right? But we can’t really do that with so many authoritarian countries. And as you say, a variety of authoritarian countries
Jessica: And countries like Turkey that actually are reasonably good at interacting with the West.
Jim: They or Hungry. Hungry is part of the NATO and part of the EU. And yet, they’re really kind of a shitty dictatorship, just one of these soft dictatorships of the sort that we could stumble into easily enough. And there ought to be standards that say that if you’re a shitty dictatorship, you can’t be a member of the open world guild, or whatever you want to call it.
Jessica: But here’s a question, I mean, something I’ve been worrying about, especially which I started thinking about recently in relation to the SWIFT sanctions, and the sanctions more generally, and what it means for the realignment of financial networks… And in particular, the generation of independent financial networks that run through Russia, China, and other nations… whether it’s better to keep rogue and bad actors on the inside, so to speak, where you have a kind of arms race of strategies, but where you can keep tabs on them and potentially have the possibility of some control? Or allow them to build… And again, this is like a big second, third-order question… or allow them to build these independent networks where they basically exclude you?
Jessica: You have very little capacity for oversight other than through intelligence channels, which may be weak. Which, if the world is devolving into this kind of bipolar state where you’ve got these authoritarian, totalitarian regimes on the one side and democratic leaning ones on the other, how… And it comes back to our discussion about really understanding the structure of trade networks and how those trade networks, even when they seem integrated, can be used as leverage, as they have been here, to control your competitors. So, how does all of this play into? Is this something that we want? Or do we want to, after the Ukraine conflict calms down, do we want to bring Russia back into our financial networks? Do we want to let Russia and China develop an independent system?
Jim: That’s a very good question. And this is a bifurcation event in terms of world history. If we exclude Russia permanently, then yes, they certainly will join the Chinese and perhaps some other countries, Venezuela probably, and build a alternative payment structure. Then the question is, does that put them at a permanent disadvantage? And is that good? Because these kinds of things are network effect. And one of the big advantages of SWIFT and the West model is that the vast preponderance of the GDP of the world is in them. So, you get the great network effect of being a member. So you have to think through this in multiple cycles, which is maybe it’s a little bit bad for our network effect to lose them. But the fact that theirs is so inferior will put a substantial negative damper on their economies forever. So therefore, we’re willing to take a small loss to the efficacy of our network and return for a big loss to them. So this is kind of a classic almost prisoner’s dilemma-like scenario, where you have to think through what you want to do.
Jessica: But it depends on whether we’re able to really develop and exploit the energy resources that we have at home and make the UN and the United States independent from Russian reserves.
Jim: We already are.
Jessica: Well, I mean, we’re moving… U.S. is, but the EU is not.
Jim: Yeah, the EU is not. Right. And of course, we have to move that direction anyway. So this just gives us a reason to move more rapidly. And the truth is, just like Iran, right? Iran hates the West’s guts, but guess what? They’ve been selling oil to us all along at market prices. And in the long term, the Russians will too, because they need the money. So I’m less concerned about their long term ability to extort around energy.
Jessica: I think we underestimate… And this is just based on observing other systems… We underestimate the possibility that Russia and China could catch up in terms of their financial networks. What’s the understanding of how long it’s going to take to really build a working SWIFT-like… China already has one… system.
Jim: That’s not hard. The actual plumbing is easy, right? I mean, SWIFT is a remarkable joke. If you actually saw how SWIFT works, it’s not a transaction network at all. It’s basically an email network, and people take the messages and type the shit in by hand. It’s hilarious.
Jessica: No, it’s not the tech. But I mean, SWIFT has a good government system. Presumably it means you’ve got this cooperative that runs things. And Russia and China who have something very different. But it’s having this sort of node to the actors as part of the system that they have to build that up.
Jim: Yep. Though, I’ll add one little point here which people forget, comparing China to Russia, as it turns out, is almost exactly the same as comparing United States to Canada. The ratios of their populations and the ratios of their GDPs are remarkably similar. And so I think we sometimes overestimate what a big stroke it is for Russia to fall into China’s orbit more fully. Because yes, it’s great to have Canada as of our allies. And they’ve been great allies, our best allies. But they aren’t a major swing force in the world. And Russia just isn’t a major swing force in the world anymore other than the fact they have nukes.
Jessica: But here’s the thing, so it comes back to my earlier remark. I alluded to a perturbation discussion. And so the perturbation in this case wasn’t… So Russia’s 12th largest economy. I take your point as kind of similar to Canada in terms of its efficacy, but the perturbation was the scale and diversity of sanctions that were applied to Russia to debilitate it. And I think that’s what we need to focus more on than the consequences to the Russian economy. We put this perturbation on the table that is a kind of financial equivalent of use of nuclear weapons.
Jim: Not yet, not yet. We haven’t quite got there yet, but we could if we embargo oil. That would be the equivalent of nuclear weapons. And that’s, by the way, what caused World War II. I mean, caused the Japanese to attack the United States is when we cut off their oil supply. U.S. was the producer of more than half the world’s oil in 1941. And when we embargoed oil to Japan, that’s basically what put them on the path to attack Southeast Asia. And then they figured, well, we have to take the U.S. out, so we better hit Pearl Harbor too. So it’s always worth remembering our history.
Jessica: Again, the question about sanctions, are these sanctions truly unprecedented in the sense that the diversity of sanctions in the package of sanctions, in the bundle of sanctions, coupled to the time scale in which they were cobbled together, coupled to the number of nations that back them, how large a perturbation is this in the sanction space?
Jim: That’s interesting. It’s not yet as strong as the maximum sanctions we put on Iran.
Jessica: Is that right?
Jim: Yeah.
Jessica: But was that over a longer time period?
Jim: Much longer period of time. So, in terms of speed, wicking it on, probably yes. But in terms of the actual severity of the sanctions, not as severe as the maximum sanctions on Iran under Trump, let’s say.
Jessica: But that does suggest that the combination of the diversity magnitude and speed does mean that sanctions have been kind of… suggest to me that they’ve been weaponized in a way that they haven’t been weaponized before.
Jim: Yeah, I think that’s fair. And then your point would be that, that’s another black swan, or at least a gray swan. That’s possible for such broad sanctions to be brought to bear very rapidly. And therefore, people like China says, “We want to make sure that doesn’t happen to us.” Right?
Jessica: Exactly.
Jim: So they then have an incentive to figure out agentically what their work around is, which is perhaps to diversify and develop a trade block that has a complimentary imports and exports. Very difficult to do by the way, but-
Jessica: Making the bipolar situation more likely.
Jim: Yes, yes. If they could, it would give them an incentive to build a truly bipolar world, but whether that’s feasible or not, I don’t know. It’s interesting. Over time, they could. I would suppose in some way and some sense, the swing power is India. India is really rising rapidly. Its growth may actually exceed the growth rates of China soon, as China slows. And India is reaching that sweet spot where its growth will continue to accelerate for a while. I think if somehow they suck India into their orbit, China would become much more capable potentially building a bipolar world.
Jessica: Well, I think one of the questions there… And again, I’m certainly not an expert on India-China relationships, but it seems like one of the questions there is, how far in the future is it that we have serious water shortages? And China is controlling India’s water, because it can.
Jim: Yep. Yep, yep. That’s a good point. And of course, both of them are going to be screwed by global warming as the glaciers melt. But first, it’ll be a windfall because water flow will increase as the glaciers melt. And then once they melt, they’re screwed.
Jessica: Yeah, there’s our third perturbation, climate change.
Jim: Yeah. Yep, that’s a slower rolling one, but one that will… If the other ones don’t get us, that’s the one that will get us in the end. That’s my cheerful thought for the day. If we don’t nuke ourselves, if we don’t drive ourselves insane with social media, then sooner or later we’ll just cook ourselves.
Jim: All right. Well, this has been an interesting conversation. Any additional thoughts, any other places we want to go before we wrap her up?
Jessica: No. I just really want to emphasize that think hard about this interaction between these two events, the pandemic and this Ukraine war with the supply chain stimulus, inflation, liquidity issues now coupled to this financial perturbation potentially weaponizing sanctions, and these realignments we’re seeing. I mean, I haven’t seen enough discussion of that, intelligent discussion about how these two back-to-back events are feeding each other?
Jim: That’s a very good point. Frankly, I hadn’t thought about that much either. Psychologically, to your point, that maybe it made us more willing to club up. Financially, certainly we deployed a shitload of our financial reserves, probably more than all of them to fight COVID. And now we’re stuck in a position with financial perturbations and much less resources to do anything about it.
Jessica: And there was so much uncertainty at the start of COVID. How right is it to blame the fed for its decisions then?
Jim: Well, I think they made the right decisions then. The question is, do they carry it on that one last cycle, was that too much? Probably. The earlier ones was pretty brilliant. They actually did a great job of limiting the financial damage of COVID, to everybody’s surprise. Remember the stock market exploded upward [inaudible 01:02:11], right? But then they-
Jessica: But it seems now to be a lot of backtracking on that in the press.
Jim: Yeah. Yeah, I don’t know. We’ll see, time will tell. Probably the last round was too much. It was probably unnecessary. And certainly, its magnitude was a little too large.
Jessica: I do think that just in terms of control, and intervention, and complex systems, the potential success of the fed at that moment, plus the development of the COVID vaccines, which of course had many, many years of work hiding behind it, our two successes that should be explored and discussed. Because we often spend our time on the failures, but if in fact the fed’s decision at the start of the pandemic was a good one, and the vaccine thing was just sort of suddenly made possible by the availability of funds to finish the development of those vaccines, we should think about what it was about those two successes that made them work.
Jim: That’s a good point. That’s a good point. And I guess, just an interesting and odd kind of question mark in history, Trump should have been able to take a lot of credit for the vaccines, right? He went all in with Operation Warp Speed unprecedented, pulled regulatory constraints out of the way, just threw money at it like a drunken sailor on leaving Norfolk. And it happened. And it’s not clear that somebody less decisive and more bound up in tradition might not have been able to do that. And yet, he hasn’t taken too much credit for it. And his numb nuts followers mostly seemed to be anti-vaccine, which is kind of very bizarre.
Jessica: I think Trump’s role in that needs more thought because the mRNA vaccine science was there really. It was just a little bit left to do. There was just a little bit left to know. Maybe it was getting it made…
Jim: Yeah, distributed, getting all the bottles made. I mean, they ramped up the making of those little vials. It turned out that was going to be the bottleneck. They increased that massively. I mean, there’s no doubt that he did as much as he possibly could have to accelerate things, and it worked. But he didn’t take much credit for it. And his numb nuts followers, don’t like it. Bizarre, right?
Jessica: Well, science is complicated.
Jim: Oh, yeah. Complicated. That hurts my head when I think about it, don’t want to do that. Oh, well, [inaudible 01:04:31] dunk on those poor people. They have enough problems as it is, right? Oh, well.
Jim: Alrighty, Jessica. Well, as always, we had a kind of free wheeling all over the place conversations, touched on all kinds of interesting things, give our listeners something to think about. And so welcome back to another fun episode at the Jim Rutt Show.
Jessica: Yeah. Thanks so much for having me on, Jim. That was fun.