Transcript of Extra: On COVID-19 Opportunities with Jessica Flack

The following is a rough transcript which has not been revised by The Jim Rutt Show or by Jessica Flack. Please check with us before using any quotations from this transcript. Thank you.

Jim: Howdy. This is Jim Rutt and this is the Jim Rutt show. Listeners have asked us to provide pointers. Some of the resources we talk about on the show. We now have links to books and articles referenced in recent podcasts that are available on our website. We also offer full transcripts. Go to That’s This is another in our series of extra COVID-19 interviews and as all the other extra interviews. The audio quality will not be up to our normal standards, but the information will be of the usual high quality. Today’s guest is Jessica Flack, a resident faculty at the Santa Fe Institute. She’s been on the show before and she’s an incredibly good thinker about complex systems, interactions between cause and effect and lots of other interesting things. Gosh, she has some interesting ideas about how the shock to the system from COVID-19 may actually provide some opportunities to move our world to a better place. So with that, Jessica, tell us about your thinking.

Jessica: Well, I mean, I guess I just want to start and Jim I know you’ve thought about this too. This should be a fun discussion. But I just wanted to start by making this point. I think we’re at a kind of unique moment in history in the following sense. So never before and it’s 200,000 years that homo sapiens have essentially walked the earth. Has there been what I would call a collective empirically informed global response of the magnitude that we’re seeing with this COVID-19 crisis. So I don’t think there’s another example when we’ve seen basically all nations more or less, all nations simultaneously face the same immediate threat. What’s so interesting about this is that the response has been one simultaneously chaotic and full of promise. That might sound inappropriate given that this is causing lots of hardship and it’s quite tragic for many people.

Jessica: But I think there are opportunities here that can be exploited to perhaps tip society into a better future. I’ll just say a few more things before letting you jump in. That is, I mean from the low hanging fruit point of view, we’re seeing innovation in our understanding of obviously epidemiology and viral dynamics and maybe even in the character of scientific collaboration. We have the opportunity to better understand how massive environmental events influence the robustness and trajectory of couple of systems like markets and economies. But there’s also something much more profound potentially on the table. That’s that perturbations, I think like this virus can potentially reveal new approaches or show the value of old approaches did as maybe out of reach or nonsensical given the status quo.

Jessica: So just an example and we can get into many more ideas. One example is, I think we’re developing an intuition that was kind of before epidemic for the cost and benefits of say democratic bottom up American style capitalism and say Chinese top down kind of capitalism. An intuition that we just didn’t have before because we couldn’t see the effects sort of in real time playing out. Of course that’s very noisy and we have biases and it needs to be worked out empirically. But we’re seeing maybe for the first time, how certain kinds of changes are driven, for example, by the institutions and social structures that we have in place much more clearly than in the past.

Jim: Yeah. The way of framing I’ve been using for these discussions about impact of COVID on the future is in the form of trying to look at where will homeostasis dominate and where will history recess dominate. For our audience homeostasis is a tendency for complex systems to return to their previous state after a shock. For instance, you get a cold, you feel like shit for three days, 10 days later you’re just fine. Very little change has happened to you a little bit at the serological level, but nothing material. The other hand you put a bullet through your heart, the homeostasis doesn’t work anymore and that event totally dominates the future. Of course that’s an extreme example. There’s lots of other more modest examples. So when we think about the complex dynamical networks that are our society, everything from the economy to education, to a marriage, to a friendship, to a scientific work, this is a big shock. I liked your framing. This is the biggest coordinated action by the human race ever. It’s got to be true. I would also-

Jessica: [crosstalk 00:05:00] the biggest quarantine by many orders of magnitude.

Jim: Yeah. By many orders of magnitude. It’s also, I would argue the biggest shock at least to the West since World War II and that was pretty damn big shock. It had all kinds of downstream effects. So, yeah, I think we will see some attempts to return to way things are, but there will also be things that will be more naturally knocked out of their current basin of attraction and into a new one. Let’s explore some of your ideas there. I think those are some of the most important and most profound things that will come out of this.

Jessica: Yeah. So I want to sort of turn that on its head a little bit and ask this question. So when we think about how we want our society to be structured and what we want to optimize, assuming or satisfies. We often talk about the degree of inequality or fairness or whatever side of the spectrum you fall with respect to issues. But we talk about specific outcomes that we would like to see. One of the things I’ve been wondering about is if instead of building societies designed to maximize or minimize certain things like the degree of inequality, could we build a society that instead optimized or satisfies for robustness and evolveability and what would it mean… How would we have to change things in order to be optimizing for those things as opposed to specific outcomes?

Jessica: I’m not saying that we right now have the capacity to really optimize or even satisfies of the level of inequality, right? I don’t think that’s something that we can very well control, but it’s the kind of discussion that we as a society have all the time. I’m saying, what if we switch focus away from specific outcomes and towards tuning mechanisms that allow us to change how robust and evolvable we are given what’s going on in the larger world, whether it’s ecological or social.

Jim: Yeah, that makes a huge amount of sense. A lot of people are starting to think that way. Because one of the things I pointed out again and again is that this pandemic with the statistical attributes of this one were entirely predictable. If one understands the fact that pandemics are a fat tailed phenomena and you plot some of the pandemics we’ve had over the last 50 years, one of this scale it’s just going to happen. Oh by the way, this is not way out on the right tail. There’ll be pandemics a lot worse than this one. I think it highlights, in fact, it shows the amazing stupidity of the hardcore game A money on money return world that works for short term efficiency and essentially tends to never invest except at gunpoint in robustness and resilience.

Jim: A tiny investment, a couple of hundred million dollars in January by the United States government in ramping up masks and ventilator production beginning at scale run up of testing. So we wouldn’t have had that first run debacle of testing, et cetera. Tiny, tiny investment on the scale of things probably would have cut the economic costs of this by a couple of trillion dollars and yet there is no signal within our current social systems that allows that to happen

Jessica: Right. But that’s true. I guess we have to ask is what would it mean to build society that could more fluidly respond to these kinds of events and also be working when everything was running well. So, for example, I mean, just thinking off the top of my head, I imagine that we would invest in technology like 3D printers or whatever the… 3D printer 2.0 that could produce infrastructure, ventilators and so forth at scale when on demand essentially. That way allow us to have a more and hopefully out of materials that are biodegradable, right?

Jessica: Because if we’re going to produce materials that we only need during a crisis and we have nowhere to store them, we don’t want to cause problems. So how could we… What are the points of entry into a system where you’re optimizing for robustness and evolveability and not specific outcomes that are not, like you say, so have we focused on efficiency? What are the things we would need to change to do that? What kind of technology would we want to be investing? What kinds of educational systems would we want to be investing in? Maybe, for example, and this is… Everyone’s talking about this now too, education that focuses on probabilistic thinking, right? As opposed to learning just standard statistics and calculus in high school.

Jim: Yep. The other one, it’s just amazing. The general public has no intuition on exponentials. It’s a staggering to me. One of the things that we were talking about before the show was the cognitive differences. How people have behaved under the information flowing out about COVID-19. I’ve come to the conclusion that there’s a huge line between those who have a good intuition about what an exponential is and those that don’t. So that’s another part of our educational toolkit. But I would go beyond just technology and hard preparedness. I would say that this has also highlighted a major flaw in our information processing. There was early signal that was available to intelligence services in the West by mid to late December. At that point, especially knowing about the fat tailed nature of pandemics, small bets should have been placed to get ready tens of millions of dollars in the United States context. In January should have been hundreds of millions of dollars.

Jim: But the information, the signal did not get through the noise and did not get to sense makers and then decision takers and then action makers. I think we have to really think through and invest not just in stuff like 3D printers and flexible manufacturing. But a more robust form of signal capture, sense-making, decision making, and then mobilization for action. That may be the thing that gives us the greatest ability to operate dynamically in an evolutionary context where we don’t necessarily know what the next big threat is going to be.

Jessica: Yeah, I mean I think that this is one of the points I’d like to make is that when we do have these heavy tail distributions, they’re different than normal distribution… Or they’re the same as the normal distribution in the sense that there’s a lot of things that are more or less similar to each other. They’re in the bulk, but there are a few things out in the tail that are rare but much bigger than you would see in a normal distribution. But they’re rare, but less rare than they would be in normal distribution. That’s important.

Jessica: One of the things that we see… So they’re low probability, significant events. One of the things that we see when those events occur is that there are second order events in the tail that are almost impossible to predict ahead of time. Because they require the first order tail events to have occurred and then their likelihood increases. So these are not things that we can forecast really, but there are scenarios that we can prepare for and we can have strategies if we know we’re entering into… If we’re in a first order tail event, we know that certain kinds of behavioral shifts that make the second order tail events more likely we know what they are. So we can check our own behavior. So these are not things we can forecast, but we can set up scenarios or scenario space and understand or develop a set of strategies for dealing in those scenarios. I think we need to see a lot more of that.

Jim: Absolutely. In fact, one of the ideas I’m going to propose, I’m going to do it here for the first time, I’ve been taking some notes to myself. I’m going to write a little essay on it, is the US government should establish an executive department of wicked risks, whose job it is to do just this kind of stuff. Who basically do advanced scenario planning for the civilian sector, to probabilistic modeling. War game, red team responses to theoretical things. Like for instance, it would’ve been really nice if we could take… Bribe them if necessary, a medium size city, 100,000 people and literally run a live drill.

Jim: What happens if you have a pandemic of this statistical attributes? We would have found all kinds of things like, “Oh shit, we don’t have enough masks. We run out of ventilators,” et cetera. Give this department of wicked risks $5 billion a year to play with and hiring the most creative, most intelligent scenario thinkers that exist on the earth to staff it. I think that would be huge for our society.

Jessica: Yeah, that’s a great idea. I think that one of my suspicions of course is that a lot of the problem in terms of responding we’re having in this COVID-19 crisis is derived from our current administration. But I don’t think this department of… Because certain things are not in place that had been in place before that maybe would have facilitated things. But we certainly having, as far as I know, we have an analog of the department of wicked risks in any administration before. I think some companies have such things. I was reading a nice article about a grocery store in Texas that’s a very big chain in Texas. I forget what it’s called, something with an H and it has essentially this and was prepared for this pandemic in terms of bolstering its global supply chain storage and so forth and is managing very well. I love that story because it’s just this… I guess not a huge company, but quite an effective one that did what our current administration didn’t do it all.

Jim: Yeah. But the other thing is, yes we can blame part of it on our administration in the United States, which anyone who listens to this show knows I’m no great fan of. But we should also note that these systematic failures of timely action were pervasive across the West. Spain, Italy, UK, France, none of them did a good job of being ahead of the curve. The only people who did a good job of being ahead of the curve tended to be either very small countries like Denmark or countries who had had a pre-run drill on the SARS epidemic. So the Eastern rim, Taiwan, Hong Kong, Singapore, Japan, and to a greater or lesser degree seemed to have done well. So yes, we have our special issues, shall we say with our current administration. But the West as a whole failed the test.

Jessica: Yeah. I think in the United States that’s complicated because I see one of the great things about the US is this sort of bottom up innovation. So everyone I know, from CEO’s to scientists is somehow involving themselves and trying to contribute to COVID-19. It’s chaotic semi-coordinated response but it generates a lot of novel solutions and local solutions. Maybe not in this particular pandemic because of the timescales, it’s not fast enough. But I think we’re going to have to wait to see whether… To sort of partition out these various contributors to where we’re at today and see how it plays out down the road. And whether maybe over the longer term is kind of more semi-coordinated bottom up innovation based strategy that the US has is useful. I just want to come back to… It’s related point. Come back to the earlier conversation about building societies and social structures that optimize or satisfies robustness and evolvability as opposed to focusing on getting specific outcomes like a degree of inequality.

Jessica: It’s not just about… To have a department of wicked risk would be awesome and to get people thinking probabilistically and to think in terms of scenarios which is a little different would also be awesome. But I think there’s a much more… There’s a profound point, philosophically profound point hidden in there and that is to really build a society that optimizes for those things rather than for inequality. We have to be comfortable with open-ended outcomes. Because we’re not focusing on specific outcomes like inequality, we’re sort of… By focusing on robustness, we’re saying we’re going to let emerge the right solution and social structure to combat this situation. That is not a typically… Even though we love innovation here in the States and we’re very bottom up that idea is not a typical idea that I think Americans are comfortable with.

Jim: That’s classic complexity thinking, right? The number of mature people in power who are capable of thinking in terms of complex systems are tiny, tiny, tiny and not zero, but they’re very small. To get that kind of response, we need to do a better job of selecting leaders and make sure that they’re up to snuff to do complexity based thinking.

Jessica: Yeah. Yeah. I mean we… But we also need to sort of come to terms or get comfortable with the idea that, if we were to build up this more fluid system and there’s all sorts of… We can have a very long conversation, very speculative one about how. I will put some mechanisms on the table on a little while. But if we were to build this more fluid system, we’d have to be comfortable with the possibility that for perhaps a short time period, we might move into a regime that’s a little bit more top down. We might put in place checks. So that sort of top down… I’m not a top down philosophically oriented person, but I’m trying to be objective here. If we optimize for robustness and evolveability, we have to perhaps accept that we’re sometimes going to enter regimes that are maybe the best regime given the environmental challenge we face. But maybe not the most optimal regime given our sort of underlying… Our ideas about how we should live as individuals and what society should… What form it should take?

Jim: Yeah. We’ve been talking about this. I got some friends of mine. What we think is that the kind of meta strategy is that the system, whatever it is, this complex view system for a new social operating system for our society to be able to deal with recurrent wicked risks has to be capable of doing phase changes.

Jessica: Exactly.

Jim: So it can be in a state that we say honors all of our deepest values, but has to be able on demand to switch into a new state. Literally a new way of operating, call it a war fighting mode, which may not be entirely honoring all of our longer-term values. But here’s the key. It also has to be a reason and a means by which that times out or which it returns to its normal mode relatively quickly once the risk has gone.

Jim: The Roman Republic had an interesting approach to this problem and they survived for what, 700 years, which was that they had an extraordinarily complicated quasi democracy, quasi oligarchy with all kinds of different veto points in the system. However, by, I think that is some super majority of the Senate and not vetoed by the tribunes. The governance mechanism could appoint a dictator and that’s literally what they were called a dictator. The term lasted exactly six months. At the end of that term, the dictator was thrown out of office and that’s how they did the phase change. Obviously we could do something more intelligent, but I think that’s kind of the idea you were talking about there, right?

Jessica: Yeah. In nature we see sort of two different types of phase changes or transitions. I mean in physics the concept is called a critical point where they’re small perturbation or small shock to the system because of long range correlations can have big effects and kick you into a new state. Sometimes we see a repertoire of state. So the canonical example is the fish school or the fish swimming together and they’re swimming together initially in soul, where they’re loosely aligned and forging. And then a predator appears, one of the fish detects the predator and this information spreads across the group. Because they’re sitting close to the tipping point by showing, by having this sort of low level of alignment, they’re able to transition quickly into the schooling state where they’re all highly aligned and escape the predator and it’s a reversible state change. They can go back to showing.

Jessica: So there the fish have these two phases essentially, they have the schooling and the showing and there’s a mechanism that allows them to move between the schooling and the showing. Depending on the detection of the predator. And of course this is a little bit dangerous because if the fish initially detects the predator or thinks there’s a predator present has gotten it wrong, they might switch the schooling inappropriately. So that’s the kind of robustness cost of sitting near the critical point. But on the other hand, it allows them to enter a more adaptive state if the fish really is present, right? So that’s one where we have… That’s one example where we have these two sort of known states at the aggregate level, each of which is adapted to a different environment, the presence or absence of the fish.

Jessica: But in other cases, it might be that you sit near the critical point and you keep your interactions and your strategies are well-tuned to the current environment, but then the environment changes and it’s uncertain or changes to a distribution that you haven’t observed before. Now you enter a state where that you haven’t been in before or you enter a kind of search space and you don’t know what you’re going to get. What you get though… You know that what you had before is inappropriate though. That’s the key.

Jim: Yeah. We use in our game be world that we’re liminal to mean that where you enter a space where you know it ain’t what it was, but you’re not sure what it is yet. That is a most interesting space. I think for the thing that you’re talking about, is probably a good way to think about the problem. The famous formation switching by birds and by fish they’re quite simple way of relating. It’s either A or B. The rule for triggering A and B is quite simplistic. As humans, we could be way smarter. We can allow ourselves to be in a liminal space for awhile and we can figure out what’s going on. Those are the kinds of capabilities that we really need to bake into our social operating system.

Jessica: Well, just again sort of playing with these ideas when things are going well actually might be the time if we could engineer these emergent systems to induce that state change to this more liminal phase. So we could explore at relatively low cost, sort of like roughly an hour just to a neutral network in biology. This quite relatively low cost alternative solutions and ways of doing things and then switch back to the one that we know works in the given environment. I mean it’s not really great to experiment when the environment is uncertain with the exception being that if you know what you’re doing before isn’t going to work in the current environment, then you have no choice. I just want to put on the table a few mechanisms. Again these are just mechanisms I’ve been thinking a little bit about in my own head. I haven’t worked on them and I don’t know if they would work. But just as examples of how we might induce this state changes, I’ll take markets as my starting point.

Jim: Let’s go for it. I love to hear these.

Jessica: Okay. So one thing I was thinking about… I think I have two examples. One thing I was thinking about is, so the market… I don’t know the history of this yet, I’m working on it. The market has these circuit breakers and the circuit breakers, I think the circuit breaker stopped trading essentially after there’s been a drop of some magnitude for 15 minutes or something like that. There’s a lot of criticism of these circuit breakers and one of the things I haven’t determined yet, maybe you know Jim I don’t, is what the history on this is and how well studied this particular solution is. Theoretically in mathematical modeling and empirically, where did this idea come from?

Jessica: It’s an interesting idea but it seems quite crude to me on the surface. So one thing I was just playing around with, and again this is just literally no work on this. It’s just something that’s occurred to me because of the ability now to measure the emotional balance in the population via social media. So computational story lab at UVM, I know, you know those guys, Peter Dodd’s and crew, have this hedonometer that they use to measure the sort of emotional valance of people using Twitter. Sadly, I think they detected recently the longest concerted, sad period in their 12 years of monitoring this. But one of the things I was… One of the ideas I was kind of playing around with the other day is what if you tethered or you made your market tethered the sort of market management strategy to something like the hedonometer. So that when the emotional… Because one of the things that supposedly drives big drops in markets and maybe in bubbles in the other direction is the emotional States of traders in the community.

Jim: Animal spirits as John Maynard Keynes called it.

Jessica: Yeah. Animal spirits, right? You get this herd effects, herding effects and contagions. I think all of that needs to be better studied. But let’s say that that is correct and roughly and that these big drops or traders following the herd essentially causing the very thing they fear to feedback. What if you tethered the market to hedonometer so that you can implement maybe shorter… You could implement time windows on trading or control the number of sales or whatever, given what the emotional balance was in the population. Of course, you have to take into account delays and many things and you might let it sort of run freely when things are going well. But when the hedonometer starts to indicate that things are getting a little boisterous or there fears taking over, you might turn that knob a little bit.

Jim: Interesting idea.

Jessica: You need a huge amount of work and empirical and theoretical work. But you could sort of tether things like markets to semi exogenous data sources like this. I’ll just put the other one on the table before, you tell me what you think of these things are or if you have any ideas of your own, I’m sure you do. Is the role of noise. So often, noise… I worry a lot about noise and randomness and how it impedes information processing and biology and effects the nature’s ability to build a systems that are well-tuned to the environment. Because basically you see errors in information processing all over the place and you can imagine one reason why that’s the case is that the world is complex and it’s hard to estimate regularities.

Jessica: So noise is often thought of as something that’s problematic and needs to be overcome. I think about it in those terms flop. But noise is also useful. And as one example, there’s a recent study in nature physics that I quite liked by by Vishu Gupta and his team and they showed in fish again that… So the fish, and this isn’t one particular species of fish. That these fish actually, when they’re sort of misaligned. The noise and the misalignment feeds back on itself, making bigger fluctuations in their swimming trajectories and actually eventually tips them into an aligned state.

Jessica: So the fish are copying or taking into account what their neighbors are doing. But that is not what causes them to become aligned. What causes them to become aligned is this feedback in the noise amplifying itself. So noise is potentially a mechanism that could be added to markets or other phenomena to help with tuning. You just often don’t think in those terms and that’s kind of an out of the box… So it’s like not an interest rate but adding randomness. So that whoever controls the market would add some random traits. That would be a really crude first past example.

Jim: People to talk to about would be Doyne Farmer and the other guys over at INET at Oxford. But we were working… When I was at an SFI, a lot of my work was done with the automated trading stuff. I actually specialized in the combination of human like strategies with noise traders and I could vary the ratios and see how the systems responded. It was interesting at some level noise traders acted as food to strategic traders, which is a little scary and it’s interesting. Yeah. What would happen if the market goes crazy? I’m just going to war game this out.

Jim: Because this idea is actually clever. So let’s say the federal reserve just for lack of any other entity, is looking at the markets and sees the markets appear to be overreacting for whatever reason. They just start introducing a bunch of noise traders, literally-

Jessica: Exactly.

Jim: … people who buy and sell and the algorithm is ridiculously easy to create an noise trader and then the noise trader will actually provide food for other traders and will tend to cause the market to stabilize. I believe that is true. It’s been 15 years since I did this work, but Doyne and his folks might actually be able to provide you with some at least modeling confirmation of that. But I like this. That’s very clever. Out of the box thinking.

Jessica: Yeah, I mean there’s a couple possibilities. I think this is not trivial at all. I mean, one is… Well, there already are noise traders, right? Already in the market.

Jim: It’s called civilians [crosstalk 00:31:09]-

Jessica: Yeah, the mom and pop traders.

Jim: Yeah. Mom and pop traders are actually… They’re worse than noise traders. All the evidence shows that they are considerably worse than noise traders on average.

Jessica: Yeah. So, I mean, so you have to drop, plus you have noise traders, this incentivizes the very smart active managers to start trading, right? Because they see the market’s now becoming a little bit inefficient, but it’s also disrupting the signal, right? The strong downward signal. So I don’t know, I think it’s nontrivial.

Jim: The other beautiful thing about noise trading is it’s very inexpensive because you’re not making any bets on the trade. You’re just basically buying and selling on both sides. So all you’re doing is paying the spread. In today’s world of highly automated trading, the spread is tiny. So I could be making $100,000 bets repeatedly for probably less than $100, right? So the actual cost of the fed to introduce noise and in fact today being paid for putting a limit order on the book, particularly in turbulent times. That God damn fed bite actually make money off of it. I love this idea, I’m going to see if I get somebody to simulate it, they could just pour on the noise and dampen the signal.

Jessica: But coming back to sort of our initial discussion before we started recording, about having a principled strategy space or family of models for thinking about the COVID-19 crisis. In the market or economic portion, this is what I would like to see some out of the box mechanisms in to the circuit breaker, tying to the hedonometer injecting noise. I just like to see… Maybe one thing to keep in mind is it could be shown in some cases that some of these mechanistically distinct, but mathematically isomorphic. So that’s another set of interesting questions. But I [crosstalk 00:32:58]-

Jim: Yeah, these are the kinds of things that our department of wicked risks ought to be working on.

Jessica: Exactly.

Jim: And yet nobody’s working on it as we know in our kind of bland, dumb, short term thinking world and that’s what we got to change.

Jessica: I did hear a little bit about this new exchange called… Is it called the longterm exchange? Do you know this? Yeah. So it’s the longterm stock exchange.

Jim: What do they do?

Jessica: Longterm stock exchange. It looks new. It’s on a mission to enable 21st century companies thrive and I think it favors direct listings over traditional IPOs. I don’t know what the… It doesn’t have much information on its website, but apparently it’s been approved as the newest stock exchange by the SEC.

Jim: Cool. I’ll have to look into it. Again, innovation. Good thing, right. Smart innovation at least and take measured risks but take risks.

Jessica: Yeah, a little bit of a move in the direction that we’re talking about. But what would it take? I mean, what would it take? Because I do think that there’s quite a deep philosophical issue here to get people to be comfortable with open-ended… The possibility of open-ended systems that might change temporary and like you say, we need to build mechanisms to make sure these base changes are reversible but temporarily into structures that maybe aren’t our ideal. I think one thing we need to do also is have mechanisms to make sure that the bottom never drops beyond a certain level. So maybe these mechanisms, this more open ended situation or optimizing for robustness and vulnerability would require that we have a standard for quality of life that must be met in a system. A minimum standard for quality of life.

Jessica: Universal income falls into this space and the idea of a welfare society. But I want to get away from the notion that this would be a welfare sites. What I’m talking about isn’t that at all. But I do think we need to have… We need to maintain some minimum level, hopefully high quality of life and then the upper end would be open. So, in such a scenario, there could be huge inequality, but if the lower bound was high enough, perhaps that huge inequality would not matter so much.

Jim: Yeah, I absolutely agree. On the first part, I am much less sanguine that the huge inequality is actually useful. Certain amount of inequality is useful. My magic number is about a factor of 20 from… In fact, I would have a very, very, very aggressive tax routine such that once you get to 20 times the minimum wage your tax at about 90%. But anyway, that’s a difference of opinion. But I do think the first part would make the… If people knew that they personally were safe, they were going to have an income, that they could have medical care, they could afford what they needed to take care of their kids. People would be more willing to allow more experimentation with some of the knobs, I think.

Jessica: Right. And just to reiterate again, I think what I’m sort of proposing here is we’re optimizing or satisficing for robustness and evolveability. We’re maintaining a lower bound that’s hopefully reasonably high quality of life. But we’re leaving the upper bound open. So that’s why I pushed back a little bit on the inequality thing because it’s not that I think large inequality is useful or not, it’s that I want to allow all of these possibilities just maintain the lower band, right? So I mean, honestly it might be the case that you could not maintain a high enough lower bound with very large inequality. That might be the case, I don’t know. But the proposal is instead of tuning for a particular outcome, you tune robustness and evolveability, maintaining that lower bound.

Jim: Good place to start. I think with that, we’re going to wrap up. This has been as I knew it was going to be an amazing intellectual ride, lots of new things to think about, lots of things to research. As usual we’ll have pointers to these various references on the episode page. Thank you Jessica. It’s been great.

Jessica: Thank you Jim. Pleasure to be on the show.

Production services and audio editing by Jared Janes Consulting, music by Tom Mueller at