How We Lost Our Sovereignty, and How to Get It Back with Jordan Greenhall

How We Lost Our Sovereignty, and How to Get It Back with Jordan Greenhall

Neurohacker Collective cofounder Jordan Greenhall joins Daniel on Collective Insights to discuss how much of today’s society is geared toward incentives that aren’t always to the benefit of the world as a whole. Greenhall goes into detail on why the incentive structure exists in its current form and why we need to change it. This starts with changing how people are educated, with a greater emphasis on helping people become more sovereign. It is this concept — sovereignty — that is talked about a great deal in this episode, including what it means and what people, and the global community at large, can gain from greater sovereignty.

Guest Bio:

Jordan is now in his seventeenth year of building disruptive technology companies.

Classic “Ready Player One” style 80’s nerd. Comics, science fiction, computers, way too much TV and role playing games. Oh, so many role playing games. Naturally, these interests led to a deep dive into contemporary philosophy (particularly the works of Gilles Deleuze and Manuel DeLanda), artificial intelligence and complex systems science in college in the early 90’s and then, as the Internet was exploding into the world, a few years at Harvard Law School of all places where he spent time with Larry Lessig, Jonathan Zittrain and Cornel West examining the coevolution of human civilization and technology.

Starting in 1998 he then tried to put all this stuff to use combining disruptive technology, movement building and a taste for going up against obsolete oligopolies. First as an early employee crafting strategy and product for, then at InterVU (acquired by Akamai) and then finally in 2000 launching and leading the online digital video revolution as founder and CEO of DivX.

After somewhat successfully navigating two financial crises and an IPO (and going down in flames at Stage6), he left the helm at DivX to return his attention to the big picture. He tried his hand at capitalism – combining Angel investment at the sharp edge of the Schumpeter wave — with participation in a number of think tanks and institutes; most notably, the Aspen Institute and the Santa Fe Institute where he served on the Board of Trustees for five sweet years.

This exposure led him to the conclusion that humanity is in the midst of a world historical transition which will likely kill all of us (see Mad Max) but just might end in a truly amazing future (see Star Trek). Getting there is going to require many things of us – most notably a significant upgrade of our individual and collective capacity for thought and action.

Full Episode Transcript:

Daniel:Hey, everyone. Welcome to the Neurohacker Collective Podcast, Collective Insights. My name is Daniel, here with Jordan Greenhall today. This is a particularly fun and exciting interview for me, because Jordan happens to be the cofounder of Neurohacker Collective. We've been working together on this for some time now, before Neurohacker, that led to [00:01:00] us doing this together. He and I were and are still working on other projects in the civilization design space, future of governance, future of sense-making, future of macroeconomics, future of infrastructure, how do we do this civilization thing better? I've been looking forward to actually getting to do this interview for a long time. I'm delighted to do it now.

Just very short background on Jordan, so you have some reference ... Much of the [00:01:30] technology that we all experience every day, in terms of streaming video/streaming audio, Jordan played a major role in that being available, a multiple tech entrepreneur in the decentralization of centralized industry space. He was on the founding team of It was one of the first plays to decentralize the music industry. Then, [00:02:00] last business venture was he was the founder of DivX, which was the first company that really decentralized a lot of what Hollywood and media were doing, by making video streaming, and so now we have YouTube and Vimeo based on that first move in the space.

Then, after realizing that decentralizing industries with tech wasn't enough to actually build better systems, by itself, he kind of retired, went to [00:02:30] Santa Fe Institute, joined the team there, became a part of the Board of Trustees, and spent a number of years studying complex systems. He already had a strong background in history and law and sci-fi and futurism philosophy, and started really thinking about how do we build viable future complex systems? He started a project there called Game B, which is if Game A of current civilization model is end of life, what [00:03:00] does Game B look like? That's when he and I met and started working in that space.

Then, when we started Neurohacker, I was actually delightedly surprised that it was something he wanted to get into, because he hadn't been working in the medicine biotech space. I think we'll start there. First, Jordan, thanks for being on the podcast.

Jordan G.:Yeah, thanks Daniel. It's fun. It was amusing coming into the office and [00:03:30] knowing that you and I, who actually spend a lot of time talking to each other are now talking to each other publicly in this vehicle.

Daniel:Yeah, and you're sitting in the seat that I'm normally sitting in when recording these there, the sign behind us.

Jordan G.:Yep.

Daniel:Okay, so why were you interested in getting involved with something that's working in the health, wellness, neuropsych, medicine space at all, because it's different enough than things like information tech? Why does [00:04:00] that seem like a meaningful thing?

Jordan G.:Well, okay, so you mentioned the notion and the distinction between Game A and Game B. I had spent a substantial amount of time taking a look at both of these things from the point of view of game design and incentive structures and, as you mentioned decentralized versus centralized technology, and how that changes people's behaviors and attitudes and decisions and capabilities. What became increasingly clear was that whether you're playing [00:04:30] Game A or Game B, you're playing these games with, and hopefully for, people. A sizable amount of what actually happens in the game is a consequence of the people who are playing.

For example, the level of wellbeing, their level of capacity. Are they suffering? Are they in pain? Are they sick? Are they limited by particular kinds [00:05:00] of beliefs, frameworks, or ideas? Then, as it turns out, Game A is in many ways simultaneously designed to not have that much dependence on the wellbeing and capacity of discrete individual humans. It's the bureaucracy. It's a fit into this particular square and all the rest of you can go away. As long as you can do your job okay, it works all right. Whereas, Game B, as it turns out, is substantially more [00:05:30] dependent on what we've called sovereignty, the sovereignty of the individuals who are playing the game.

Then, just to go one more step, I think largely as a consequence of the fact that Game A doesn't care that much about the wellbeing of the individual human beings who are part of it, it doesn't need them to be well rounded and capable, it also tends to produce quite significant limitations and constraints in human capacity. We end up in a situation [00:06:00] where, even if we're reasonably effective in building out a lot of the other elements of Game B, say, for example, an alternative economic model, if the human beings who are coming out of Game A, don't have the ability to play Game B, for whatever reason, then it's a nonstarter. That was the impetus for me, at least, to begin looking in this space. Then, of course, that's where you had spent a substantial fraction of your life.

Daniel:[00:06:30] You said, if the people don't actually have the wellbeing and the sovereignty, those were key terms, to be able to play a different game — in Game A, a person's ability to be productive within a narrow niche matters, and that's kind of all that matters — their ability to be healthy, whole, sovereign outside of that narrow niche ... Since the narrow niche usually doesn't require them self-assessing what needs done outside of the narrow boundaries, [00:07:00] we can actually squish people into narrow AIs or robots, right?

Jordan G.:Right.

Daniel:This is very different. I mean, this is almost like the intersection of education and personal development and health altogether, right?

Jordan G.:Yes, yes, I think that's right, and I think that it's funny, in fact. The fact that we've partitioned those into three different domains is part of the problem.

Daniel:Speak to the future of that. [00:07:30] What's different than saying the future of medicine, when we say the future of wellbeing science?

Jordan G.:Okay, so for reasons I think both good and bad ... For example, and we could do this in education or personal development, medicine, it's part of the analytical methodology, right? It's taking a whole bunch of stuff and decided this is not part of medicine and we just focus on these subdomains. The health of the physical body and, in particular, the lack [00:08:00] of a named sickness of the physical body, is the domain under investigation. That's major move number one.

I note, by the way, that psychiatry, for example, is a branch of medicine that takes into consideration the presence of certain kinds of named maladies in the mind, but, of course, it also does it through the channel of the body as the primary mechanism. Then, intriguingly, for reasons [00:08:30] that we probably don't have time to go into, these kinds of moves in Game A also tend not only the analytically narrowing to very specific prescribed domains, they also tended to grab particular tools and use those tools to the exclusion of other tools. What happens in medicine then is that we get a combination of a handful of tools that are diagnostic and [ameliorative, inaudible 00:08:53] in nature, pharmacology being a primary one, and surgery being another primary one. Then, [00:09:00] what happens is you get this nice trade-off that, to the extent that there is a named problem in the body, a disease, for which these tools work, medicine is — check — good to go and can generally actually provide pretty high quality solutions.

To the degree to which there is either an inter-domain problem, something that's happening between, say, medicine and education, or trans-domain problem, something that doesn't actually currently have a domain at all that's ascribed to it, or something that has [00:09:30] characteristics that are not particularly amenable to these tools, then we find ourselves in a situation where the approach of contemporary medicine ends up being limited and, oftentimes, even counterproductive. We can unpack that and create examples of that sort of thing over and over. I mean, diabetes is a case that medicine itself has already identified.

Within the medical toolkit, diabetes shows up, first and foremost, as something that can be resolved through the intervention [00:10:00] of insulin, and, at the medical level, that's actually a pretty good solution, but what we see, of course, is that diabetes is a complex phenomenon that includes everything from what kind of choices individuals make in what kinds of foods they eat, what kinds of health, what kind of fitness regimen, sleep regimen, what kinds of other kinds of behaviors that's engaged in, who the social environment they put themselves in, et cetera, et cetera, et cetera. All of these are problems that medicine has defined as out of scope, out of domain. [00:10:30] Then, you might kick it off and say, well the healthcare industry — notice that they rebrand it as the healthcare industry — has endeavored to figure out how to address the larger combinatorial of causes associated with diabetes and is actually self-conscious of the fact that it does a rather poor job.

Health ... Behavior change is a thing that's been around now for decades and is, more or less, identified in health care as just a hard problem that hasn't been solved particularly effectively. [00:11:00] Of course, diabetes is an easy one, but there are much larger ones that we can actually grab that are even less amenable to medicine, yet nonetheless, are fundamentally identified as things around wellbeing and human capacity.

Daniel:Okay, so, I'm fishing here, but why is behavior change so hard, when we look at a bigger picture? Say, we take diabetes. Why is behavior change off of eating too much sugar, too many carbohydrates, not enough nutrient-filled food [00:11:30] and exercise, within our larger macro system, so not just within medicine, but everything that's conditioning that? Why is that so hard, and a related question of ... You say, we wouldn't have time to go into it fully, but that medicine ends up narrowing to just having certain tools, right? Then, why does it have these tools and not other tools? Obviously, we're getting into economics and incentive, but that's worth speaking to.

Jordan G.:Hmm, yeah. It actually hearkens back to this notion of different games, because [00:12:00] at least part of the answer, and there's many different aspects to this question, but at least part of the answer is identified by the name attractor or basin of attraction. I'm actually going to shift from medicine for a moment, so we can see the whole different perspective. Let's take a look at education.

It's relatively well understood that the American educational system has challenges. One of the things that many people who try to do reforms in education notice [00:12:30] is that they have an experience a little bit like trying to push a heavy ball up a hill, where they get it, say, three quarters of the way up, but then, as soon as they let go, the ball rolls all the way back downhill. The reason for that, there's actually a basin of attraction of a lot of different kinds of forces.

For example, in education, you have the linkage between what's called credentialization ... Let's just say, for example, you go to school to get into college. You go to college [00:13:00] to get a good degree. You get a degree, which is to say, you get a good credential, so that you can get a good job. You actually have this binding between the labor market and the education market, that actually makes it so that things that you do in education, if they actually show up as not improving people's job prospects, won't work. They'll just be eroded away. They're the rolling downhill of the ball in education.

We can actually identify other kinds of domains that reinforce each other in this fashion. What ends up happening is that, in many ways, Game A [00:13:30] has evolved over time to be one gigantic self-reinforcing basin of attraction. Past certain minor limits, if you push really, really hard against something in one subdomain, again note, coming all the way back in medicine, you can make a lot of attraction in getting people to take insulin, but if you're not dealing with things like, say for example, the media and advertising industry that is hitting everybody's brain constantly saying, "Eat junk food," or the junk food industry [00:14:00] that is modifying the content of food, so as to maximally hijack the way that our brain interprets what is a good choice — Tristan Harris calls this hijacking evolution 1.0; you and I talked about it in terms of hypernormal stimuli — then, you're screwed, right? You end up with a whole bunch of human beings, who are taking insulin, but are in fact eating food that's bad for their bodies and being unable to make those choices.

[00:14:30] It's one of these weird things where you actually have to be able to grasp the complexity of the whole problem, and then, as a single movement, get the entire system beginning to shift very, very subtly, by the way, and notice which pieces are pulling, which pieces are pushing, modify here and there, until in fact you've engineered or developed, in fact in some sense nudged, the system into a new place. Then, when it's in that new place, that new place is, in fact, stable, and it'll hold in that location. You're no longer worried about the ball rolling down the hill.

[00:15:00] That's actually, to look back, why I moved from where I was into the domain of wellbeing, which was that I had identified that, while we are actually making really good progress in places like, say, blockchain, in moving economic systems and in decentralized media and software and moving, say, media systems, I at least wasn't at the time aware of anything that was meaningfully being done in this domain of wellbeing. These things are all connected. We actually have to be really [00:15:30] thinking about all of it, at once, and how they all fit together, if we want to make this transition from A to B happen.

Daniel:Okay, so you hit on a really core topic that I just want to highlight. For people who haven't thought about this much, it sounds profoundly cynical, but it also is inescapable. From the business supply side, addiction is profitable.

Jordan G.:Sure.

Daniel:If someone is addicted to the stuff that I sell, I'm going [00:16:00] to sell more of it than if they have the ability to say no and not take it often. Whether we're talking about food ... If I'm selling more addictive stuff, then people are going to eat it more often, and if I make more money by how many times people buy my thing, maximized lifetime revenue of a customer, then I have a financial incentive to optimize towards maximum addictiveness. Interestingly, I'm going to figure out how to market in the most compelling ways, because behavior change actually isn't hard there. They were [00:16:30] pretty good at getting people to eat the shitty food, right?

Jordan G.:Right.

Daniel:Then, the fun thing is ... I mean, the fun, terrible thing is then that actually predisposes them needing the medicine, and the medicine companies also make more money when you need more medicine. As the people get sicker from eating more food that they're addicted to, and then get addicted to, meaning dependent upon, the diabetes medicine or the statin or whatever it is that came from that food, GDP goes up in both cases.

Jordan G.:[00:17:00] Right, yeah, I think there's actually two ... Well, there's a bunch of stuff in there, but let me see if I can tease two things out. One is the fact that, because of some of the deep characteristics of Game A, which one of my collaborators [inaudible 00:17:21] identified as money on money return ... The primary way to win Game A is to increase the [00:17:30] rate at which your money is making more money. I say that because, if you look at the slope of Game A, over the past 50 years or so, maybe 80 years, what you'll notice is that there's a gradual and continual slide towards that direction.

Let's say, for example, to put it very prosaically, in the beginning the rule might be something like "do the right [00:18:00] thing." Then the second rule might be something like "make as much profit as you can," but what ends up happening is that somebody who plays by that rule compared to somebody who, say, plays by the rule of "make as much profit as you can and also do the right thing" ... All right, so that minor shift of orientation means that the person who plays by the second rule is going to actually make more money, and, by virtue of doing that, is more likely to be able to, say, get more access, more power. They'll go up the ladder. They'll have more choice making [00:18:30] and, of course, they'll have more money with which to make more investments, but it's not a very long step from "make as much profit as you can and try to do the right thing" to "make as much profit as you can and, say, do it as legal."

That was actually a move. That move actually happened. Then, you've got something along the lines of "do it as arguably legal." Then, it's not too far to say, "Well, do what you can get away with." Then, maybe "do what you ... [00:19:00] where getting caught is less expensive than not getting caught" or more than the profits you make by virtue of doing what you're doing, and then even to the point of where the costs of bribery, corruption, greenwashing, manipulation, et cetera, is less expensive than the benefits of playing the other way. It is in fact a race to the bottom, a downward slope.

The problem is that, at each step, the underlying intrinsics of what kinds of behaviors are rewarded in Game A [00:19:30] leads to movement down that slope being actually showing up as a winning strategy. Of course, then we end up with what I think many of us observe today, where a person who runs a pharmaceutical company, who does not in fact jack up prices to the highest they can possibly get away with, is in fact a loser and will end up either being bought out by somebody who's playing more aggressively, being thrown out by their shareholders or board of directors, et cetera, et cetera.

This is a [00:20:00] ... It's not a necessary characteristic of the way that human beings operate in the world, but it turns out to have been one of the characteristics of Game A, which had lots of virtues, which should be quite clear, like the way that Game A was designed, and the fact that it ended up winning in the 20th century showed up lots and lots of positives. What we're observing now is not that Game A was always a terrible thing, but rather that there's certain characteristics [00:20:30] of that style of play that ends up in a bad place. Now, the effort is to say, "Okay, how do we, while we still have a reasonably safe place to do this in, figure out how to actually transition to some other kind of game, which hopefully is in fact one that doesn't naturally end up in a bad place by doing what it does?"

Daniel:I.e., we engineer the basis of attraction properly of the whole system dynamics upfront.

Jordan G.:At least we endeavor to, try to at least [00:21:00] be mindful of it, be thoughtful of what are the likely places where this thing ends up as it gets to maturity. What are the underlying characteristics of what winning plays look like for individuals and groups? It's actually called niche construction, so we would in fact want to construct the niche, so that as people attempt to figure out how to do the best they can in that niche, their choices, their local choices will always tend to actually [inure, inaudible 00:21:28] to the global [00:21:30] best answer.

Daniel:For anyone who's listened to the podcast a lot, you will hear that two of the three major areas that Neurohacker focuses on in hoping to do things in the health and wellness space, working to do things in the health and wellness space that couldn't be done in the primary medicine space right now are, one, that the financial incentives in the current system are wrong. He was obviously just [00:22:00] speaking to that, which is if someone who is ... If preventing illness ends up meaning that you don't sell your product, and treating/curing illness quickly means that you can only charge as much as you have for a short time, but managing the symptoms of illness for a very long time is very profitable, that's a perverse incentive system. If treating the side effect of a drug that you give someone involves them having to buy [00:22:30] another drug that you also make, and it's called an upsell, that is also a problem.

We've focused on is there a way that we can actually get out of the financial incentive trap that most of medicine research is in, and then also that the epistemology wrong, meaning it narrows too much. Let's call this a nameable disease, and let's find one synthetic molecule or one surgery that will be able to correct some symptomatic part of it, as opposed to looking at the more complex set [00:23:00] of dynamics and how can we work with the complexity that's generating them? Just appreciating that, as Jordan's talking about this, he's naming some of the core principles of what Neurohacker's endeavoring to do.

I wanted to say, when you said money on money return ... That brings up the thought of financial services, and that people start mistaking production and extraction as one of the dynamics that financial services cannot [00:23:30] meaningfully increase the production of the types of goods and services that increase the quality of life of everyone, while still extracting a lot.

Jordan G.:Sure.

Daniel:This is one of the main things that has made blockchain so exciting to so many people in the last few years, is not just to decentralize anything, but largely to decentralize financial services for this reason, and so this is an area that you have worked in a lot, and you are also talking about how do we get the incentive structures right for things like diabetes. I'm curious, as you think about [00:24:00] the role that things like blockchain could have in changing the financial structures and the incentive structures in medicine, health, wellness, education, some thoughts to share on that.

Jordan G.:Wow, okay, so there's a lot. Let me see if there's a handful that I can put together that would be interesting and useful in this context. All right, so there's a couple of core characteristics of the notion of finance in general, [00:24:30] and I think it's actually interesting to drill down on that, because money isn't actually anywhere near as obvious or easy as people think, because we're so around it all the time that we think, well, money is an object. It used to be, in fact, a physical object, like a coin or piece of paper, that I get for doing stuff and I give to [inaudible 00:24:51] you do stuff for me.

All right, so okay, it's prosaic. It's simple. It's well understood. What's really interesting to think about is that money [00:25:00] represents the ability of human beings to abstract. It represents the ability to take something which is a sign of something and replace it for the thing itself, all right? Instead of having an apple, what I can do is I can have ... I don't know what apples cost these days, two dollars, and those two dollars represents an abstraction, the potential for me to get an apple, if and when I want it, and, of course, it's extraordinarily [00:25:30] powerful, which is what finance is about.

The problem is that you've now got this interesting gap. You've got the gap between the thing itself, the value, and the indicator, the sign of the value. What happens is that it's not long before somebody realizes that you can actually make this show up like crazy, without having any meaningful impact on this, and that is just what I would just characterize financial services as being, the insight that if you're attempting to optimize for money, completely [00:26:00] regardless of the degree to which the money is related at all to an optimization of value ... I should point out, by the way, that there is a meaningful amount of tomfoolery in economics, where economics tells a story that there is something irrevocable about money and value, that they are directly and always connected. I think it's important to recognize that that's not the case. They can be, and so this is why money is useful, very useful, but they also can be separated.

We see [00:26:30] this, for example, just in the simple notion of debasing a currency. If I can counterfeit a bunch of money, I have generated lots and lots and lots of the sign, but I haven't generated the value. I think, in many ways, what ends up happening is that financial services ends up showing up a whole lot like counterfeiting. They produce lots and lots of things that generate lots of valid signs, lots of money, but in fact little or no value, in spite of the protestations of the economic profession.

[00:27:00] Now, another piece — and I'm trying to go two pieces, and then shift to blockchain, just to create the current parallax effect — is that another thing that happens with money is that, and money is an allocation of the kinds of choice making that we're investing in, in our economy, which is to say that every dollar you have is, in many ways, a vote in what the economy does, all right? If I really, really want to have nothing but [00:27:30] red Ferraris, and you really want to have nothing but, say, corn, and I have all the money, then the economy is going to produce red Ferraris and not corn. What ends up happening is that the way that finance allocates money also shows up as a way that our society allocates choice making, at least in the economic domain, and different ... There's no specific reason to believe that the people who are most capable of playing the game of finance [00:28:00] are also the most capable of making good choices in what the economy should be producing. In fact, there's very good reason to believe that's not the case.

Now, shifting over to blockchain, think about what those two characteristics that I just articulated show up in blockchain, and then we'll move to the third, which is, I think, the most important. On the one hand, because blockchain is the kind of thing that actually doesn't make a whole lot of sense to people who haven't done things like study cryptography or have a deep, [00:28:30] deep sense of technology and technology trends, the people who showed up as being the earliest winners in the blockchain space are a different population than the people who have been winning the finance game for the last 80 years.

Now, of course, the finance folks are scrambling like crazy to figure out how to reestablish their dominance in the blockchain space, but at least right now, even though blockchain is unfortunately rather characterized by concentrated wealth, it's also characterized by concentrated wealth in the hands of a different set of choice makers, who [00:29:00] at least so far have a higher degree of capacity to perceive real problems and compose real solutions. To put it a little bit prejudicially, these are the engineers from the movie Apollo 13, who know how to solve problems. That's actually a much better place to put your choice making than in the hands of people who have optimized for manipulating and counterfeiting money.

Then, secondarily, there's a big difference between [00:29:30] money, as we currently understand it, and the way that the blockchain shows up, that I actually remember thinking ... Way back, when it was first starting, there was a quote, that I read about, from a Roman Emperor, who was telling his son why it was okay for the emperor to take taxes from the people who did sanitation/sewage, and he said, "Gold hath no smell," meaning there's no traceability to it. There's not any real direct connection between [00:30:00] fiat currency and records.

Of course, what that does is it creates a great niche for exploiting that fact. All right, so if person A shows up with a million dollars in their pocket, and person B shows up with $100,000 in their pocket, person A gets much more power in the economy than person B, in spite of the fact that person A may be, for example, a criminal, somebody who stole that money. You don't really know. It has no smell. It has no ability to be traced; whereas, blockchain is all about durable records. It [00:30:30] is. In fact, the whole point is that it is a ledger, decentralized ledger, that is as resilient as we can currently conceive against modifications of the records themselves. This, I think, is both true at a technical level and at an ethos level, but there's something about the ethos of the blockchain community that thinks about keeping good records as being important.

Now, by the way, to be sure, a large number of folks in the blockchain community also very, very much want to be off, in particular, the government's [00:31:00] radar, but I think that's actually subsidiary to the underlying foundation of the technology, that it actually does enable us to have more ... I think Dan Jeffries, actually, had a really wonderful blog post about the blockchain as being the third major new emergence of a kind of accounting, which he calls triple ledger accounting. That's actually worth deeply, deeply looking into.

Then you get to [00:31:30] the last piece, which is frankly, I think, right now, still very esoteric, but I think worth trying to scratch the surface on, which has to do with the way that blockchain enables us to use money as a variable in a software systems code. What that does is allow us to actually be thoughtful about designing motivational, and by the way game theoretic, choice making infrastructure, so as to solve this [00:32:00] problem we talked about earlier, the problem of how do you actually move high variable, complex systems from one basin of attraction into another basin of attraction. We can actually do this right now, with a very simple example, which is Bitcoin itself, as the first major instantiation of blockchain.

Bitcoin was able to solve a problem that, up until that point, had been completely unsolved. You can imagine, for example, let's say, PayPal. PayPal was a pretty successful company, and it had ... I mean, if you look at the roster of folks [00:32:30] who are associated with PayPal, there may not be a better pedigree. Yet, in terms of the scope of what PayPal endeavored to do, which, in their case, was to create a new form of money or digital money, it still has not yet done anything other than what you can consider to be failed. PayPal had some of the best people civilization could muster at a pretty good timing and failed. Whereas, Bitcoin, more or less designed by, say, three or four people, in its original [00:33:00] state, seems to have succeeded.

There is actually an accelerating community of people who are using this thing and constantly solving problems and fixing it and building it out. The way they did that was by understanding that they were actually dealing with a complex system, and so they designed a technical architecture that had a motivational infrastructure, so that individuals, coming from wherever they came from, would look at it, choose, as individuals, to make choices that were in their best interests, [00:33:30] but because the way the system was designed, those individual local choices would always aggregate to something that is in the global interest of the system itself. I mean, we could double click on that and try to get some more detail, but I think now's a good time to pause. The point is that that's an example of how this new kind of fiscal software, I think some of the folks at [inaudible 00:33:56] are calling it socio-technical platforms, actually enables [00:34:00] us to crack the code on designing complex systems to actually be able to move things out of basins of attraction into hopefully higher levels of overall capacity.

Daniel:Right, so with blockchain, two of the really interesting things are the incorruptible or harder to corrupt ledger, but then also the cryptoeconomics, and those are two different things. The cryptoeconomics is the ability to have a more [00:34:30] nuanced and complex incentive structure, because rather than just dollars that are going to be associated the same across the whole market as a decentralized incentive, you can have different types of tokens for different types of things, et cetera. If we relate this back to, say, some of the issues we were looking at with the financial incentive that went down the game theoretic hill that you were talking about that started with "do good things and be profitable," [00:35:00] to "be profitable and maybe do good things," to "get away with it," how could this type of cryptoeconomic dynamic play out in, say, pharma or in hospitals or in citizen science or anything like that in a way that could actually change the motivational dynamics that would lead to better health care?

Jordan G.:Right, so, as you know, there was an announcement, I think today — it may have been yesterday — where [00:35:30] some hospitals are proposing that they may begin the process of endeavoring to create an alternative scientific and economic model for producing pharmaceuticals. This is a response to the fact that pharmaceuticals are too expensive. I think actually the technology, the blockchain technology, and the concept of a decentralized autonomous organization is, in fact, exactly the right solution to this problem, and, in fact, if I could figure out a way to message this to the hospitals [00:36:00] that are doing it, this would maybe be the best thing they could possibly do.

First, let me shift a little bit to the software domain and then come back to the pharma domain, because I know the software domain better, but I think it's a direct mapping. One of the things, for example, that you'll see in one of the blockchain — core blockchain infrastructure at play is called Ethereum — is that, in Ethereum, what they've actually created is their own private software language, called Solidity. It's kind of like JavaScript or C or C++, meaning it's a language [00:36:30] that software guys can write in, and what they write will show up as something that the Ethereum system knows how to understand and can do things with.

Now, all code written in Ethereum is in some sense intrinsically open source, meaning that if I write a very powerful object in Ethereum, you can actually write something, which calls that object for free. It's just there. Now, of course, I can make it not for free, but the point is that it's in the system, so [00:37:00] what ends up happening is you get this process where, as more and more core infrastructure is built and made available, the next layer of innovators don't need to reinvent the wheel. They don't need to rebuild that core infrastructure to get to work on top of that core infrastructure. In fact, one of the primary problems is finding the tools that you need, out of this giant and increasingly large pool of tools, to be able to solve the problem that you want to solve, but this is very ramifying, right? The idea of standing on the shoulders of giants begins to happen very quickly, when it's [00:37:30] all sitting there as software, all sitting in a blockchain registry, which means that all the records are well kept, and the path of who did what is actually fully traceable.

Who did this? Well, I can just find it. It's just literally living there in the blockchain, because that's what the blockchain does. In the case of Ethereum, you can actually write contracts in software, pieces of software that process if-then statements that can trade money back and forth. Daniel can write a piece of code. He can submit that code up to Ethereum, and it says, "If you want to access that code, here's the API [00:38:00] call to make that will send me a very small amount of ETH, and in exchange you can use the code." They're actually building an internal economy that incentivizes software developers to be able to fully build the most valuable and most shareable software that are of benefit to the entire community, and be fully incentivized and motivated and rewarded for so doing, which, of course, should create a massive shift in the velocity of how software is developed.

Now, of course, you could do exactly the same thing in the category of pharma. You can create a mechanism whereby, for example, [00:38:30] all the data lives in a shared and appropriately permissioned open database that has Ethereum contracts giving permission to access that data, where experiments and all the results of experiments, even in medias res, so that you don't have to actually go through an entire experimental protocol, publish it, scrub it so that it looks good, and then hopefully get it into a journal. You can actually just have that be in an open environment, because the people who are doing the work have an incentive that is not tied to, for example, publish or perish, right? They have [00:39:00] an incentive that is not tied to creating patents, but they have an incentive to moving forward the state of the art in science.

You can create neat little Ethereum contracts that actually reward people for, say, very high quality experimental design. Just submit a high quality framework and, poof, bam, be rewarded for it, and everybody who uses that framework, you get paid for this open source framework that you've generated. Of course, the same thing happens for data. If I come in, and I'm saying, "Hey, well, I can't really contribute meaningfully to [00:39:30] the science. I can't contribute meaningfully to the software, but I can engage in experimental protocols. I'm willing to submit myself and put my data into this large pool."

Maybe what I do is I ... Let's just say I sign up for a sleep study, and so I wear an Oura ring, and I have an app, and it's tracking my sleep. I just every day submit some additional data, and the key is that my data gets put into this shared database, and all the variables associated with my data are now available for other people to research, and I'm also in a pool, so I get a message, [00:40:00] "Hey, would you like to participate in this particular sleep study for this particular practice? Here's the reward. We already researched your data that indicate that you already qualify for our protocol." The protocol, literally in software, has the ability to make it ping out to the database to identify particular individuals and make the offer on its own.

It's kind of like a lot of the thinking that's going on in the IOT space, the Internet of Things space, happening in the Internet of Wellness space. What ends up happening, then, is you have an increasingly autocatalytic, [00:40:30] an increasingly architecture based, meaning that most of the hard work has already been built as a platform that people could just access and resource, and all the innovation work is actually being done at the surface of the sphere. As we know, the volume of the sphere increases to the cube, so you've actually got massive return on the investments being done at the outside.

Instead of having lots and lots of little spheres that are all communicating with each other over the market, everything's happening on the inside of that sphere. I'm [00:41:00] sorry. All the value's happening inside of this sphere, and it's being shared as a commons resource out into the broader population.

That's the sort of thing that I think is frankly well within the scope of doability now. I mean, it would take meaningful effort, but if you're looking at the size of the amount of money that's currently being, frankly, wasted in the interface between hospitals and pharma, on the order of, say, God, it probably wouldn't even be that much, on the order of hundreds of millions of dollars a year, would be vastly more [00:41:30] than enough to completely resource the infrastructure that I'm talking about and almost immediately, frankly, you'd get some returns. In three or four years, you could probably be replacing 20% or 30% of what's going on in pharma.

In seven years, what'll end up happening, actually, is that you'll be shifting. You'll basically be decoupling financial services from the science of medicine. What'll end up happening is that the scientists will be radically liberated to focus on what they [00:42:00] do, and, by the way, the engineers and technologists, too, because there's obviously a lot of building of instruments and tech that's fundamentally required to do this, but the resource flow will no longer be gated by what, effectively, is a gigantic financial services business sitting on top of what should, in fact, be a science and technology project.

Daniel:It sounds like the key thing that you shared in there is the increase in sharing and transparency, and thus collaboration, and thus collective intelligence and collective capacity, [00:42:30] where the current incentive structure incentivizes owning and hoarding IP and making sure nobody else uses the things that you discovered, because you're going to make your money on patents, and not sharing what you're learning until it's published, because the whole thing is published. Really what you're talking about is the ability to change the information ecology, the incentives that change the information ecology from ones that incentivize hoarding information and [00:43:00] making it hard for other people to use — they have to pay for a license — and even disinforming, to one that maximizes informing, sharing, and collaboration.

Jordan G.:Yeah, and I think there's actually two key pieces to that. The first we've talked about a little bit, which is the ability to keep records, or as our friend, Michael Vassar, talks about it, the ability to actually deliver justice, which he defines as making sure that the loops are closed, the value created needs to be value returned, and that externalities [00:43:30] need to be returned to the creators of externalities, all right? If you have injustice, if you have bad records in a system, if you don't have the ability to determine who created how much value and who created how much externality and thereby return it, then you get a system that drifts quite rapidly, and where a lot of strategies are about stealing credit and avoiding responsibility.

That's one piece for this, and one piece is just radically increasing the quality of the records that are being kept, and therefore closing more and more loops, which is to say creating more and more justice. [00:44:00] Then the other side of the equation actually has to go to stuff like-

Daniel:As soon as you say "more justice," you also mean more incentive to actually do the right things rather than the wrong things.

Jordan G.:Yeah, and intrinsically, just very simply. It's not that people have to become more pro bono. It's just that the good things they do will be noticed and rewarded, and the bad things they do will be noticed and punished, done. It's pretty simple. That's straightforward. As long [00:44:30] as you can provide a framework where people have clean boundaries, and good choices are awarded and bad choices are punished, they will begin to move in that direction, and they'll begin to move in that direction en masse.

The other has to do with the notion of the theory of the firm-

Daniel:Before you go to-

Jordan G.:Oh, go ahead.

Daniel:Theory of the firm-

Jordan G.:Go ahead.

Daniel:You and I have had the benefit of having Michael Vassar spend a lot of time explaining this model to us. I think a lot of people think that markets [00:45:00] do what you just said, that we live within capitalism, capitalism's based on market theory, and that markets are supposed to reward the things that are good and not reward the things that are bad, and therefore you get a natural evolutionary dynamics of good stuff, and it's kind of how evolution itself works.

Jordan G.:Sure.

Daniel:Why is that not true? Let's just assume that someone's listening to this, thinking that markets already do that. Why is that not currently the case?

Jordan G.:Well, I think a big part of it has to do [00:45:30] with this notion that gold hath no smell, meaning that, again, person A shows up in the market with 10 apples, and person B shows up in the market with five apples. The fact that person A stole those apples from person B is simply that the market may have no capacity to proceed at all. In fact, we don't even think about that as a market transaction. That's called justice.

What we say is, "Okay, well person B then needs to find some way to sue or otherwise rebalance the underlying infrastructure," so what [00:46:00] we think about then is that the market is consisting of a whole bunch of little circles that are communicating with each other through transactions, and it doesn't actually have any information outside of that information flow. It has an inability to perceive all the different ways that somebody might actually falsify the stuff that the market actually needs to be able to make good choices, meaning that if you think about the game, like they start off with "do the right thing," and it slides all the way down. [00:46:30] If everybody who's playing the market game is self-enforcing to do the right thing — social norms really, really work, and anybody who plays in anything but the most virtuous way is selected, again, through their normative channel, then the markets will actually tend to do a pretty good job.

Well, there's more to it than that. I mean, there's a whole bunch of other stuff to think about, but that's one that we can focus on right here. Since markets actually have very little ability [00:47:00] to perceive that kind of a thing that they outsource that to other areas, social norms, laws, et cetera, that's the channel you gain. All right, you gain that channel, and so you show up as a really great market player. You're a bank. You've got a giant fucking building with marble columns and actually completely covered in marble and have trusted people wearing fancy suits, that all signal certain things that the market can perceive, but the gap between signal and the thing being signified is something the market has effectively no capacity [00:47:30] to perceive at all, and that, then, becomes the game.

When you move more and more and more power and choice making into the market, you end up basically creating a niche for gaming what the market can't perceive and simulating what the market perceives as being a good answer. Then you're on that slide, right? Do what is most profitable, highest money for money return. The market sees that as positive signal, and you're riding the sleigh down the hill.

Daniel:Is there more on that?

Jordan G.:[00:48:00] Damn sure, I mean there's lots more. Do you want to keep exploring that space?

Daniel:No, I think it's good. I think it's important for ... I think most people today have some sense of how much greenwashing and various forms of we are saying we're doing a good thing as part of the marketing budget more than the actual product budget of really doing a good thing proliferates, and I don't think most people think the amount of money that's been made in derivatives as a market corresponds to [00:48:30] real goods and services that benefit the lives of most people.

Jordan G.:Right. Let me just ... We can actually say this extremely simply. If people who are in control of the money supply printed all the money and gave it to themselves, the market would have absolutely no idea and no way of responding to that fact, right? It's like [00:49:00] the brain and heroin. By itself, the way the brain responds to simulated neurotransmitters, it has a really hard time being able to tell the difference internally. The only way you can respond to the notion of mass counterfeiting of money is through a completely different channel, not known as the market.

Now, of course, you could try to invent ways to simulate that. Okay, well, all right, fine, what we'll do is we'll create agencies that we're calling anti-counterfeit agencies that we will pay to enforce this. We thought, [00:49:30] okay, cool. Now, what we're doing is we're trying to create market mechanisms to instantiate other kinds of social functions, and that's a second order solution. We should be very mindful that it's second order, not first order. It actually requires us to be thinking about this different modality and then using market mechanisms to do it. What we end up in, then, is a regression.

Daniel:Then, of course, you have the scenario where the lobbyists that are making the laws are getting paid for by somebody, and that means they're getting paid for by the groups that have enough money to pay for them, that then work on creating legislation in their [00:50:00] own interest, and the campaign budgets for the politicians, and the et cetera, et cetera.

Jordan G.:Right, and this again gets back to that notion of justice, injustice, and record keeping, that if you actually happen to have ... Well, there's a limit to this, but if you happen to have something that was just really, really good recordkeeping, and you have really high quality ability to measure who's doing what to whom, what are the various interests, and everything else, then the ability for, particularly, a decentralized system to make good choices, a marketing system, is relatively high. The less high quality [00:50:30] of recordkeeping, the less high quality or ability to perceive reality and have a history, a real history of what's going on, the less effective those kinds of mechanisms are going to be. Then, of course, there's the actual limit, which is-

Daniel:That's where blockchain is actually valuable.

Jordan G.:That's where and why blockchain is a very interesting solution. The other piece is just the limits of understanding that, past a certain amount of information velocity, you just get lost in the fire hose, [00:51:00] no matter how accurate your records are. Let's assume there's a 100% chance that, with an adequate amount of investigation, you'd be able to know that I had just cheated you, but that so much craziness is going on constantly that I'm also quite able to make a bet that I can cheat you in the likelihood that you're going to be able to traverse the information flow, within the time that it's worth to you and with the attention that you have, to close the loop on me. That bet's going to keep being made.

What [00:51:30] will end up happening is we'll basically invert it into the defraud equivalent of high speed trading, which may, in fact, just be defraud. It may not be the equivalent. High speed trading may just be fraud, but the point is that I can defraud you so quickly and at such a low cost that you can't actually close the loop, and therefore again I've found another solution to the problem.

Let's get back really quickly to the notion of Coase, because I think it's actually quite interesting in the concept of thinking about how this shows up in places like medicine and [00:52:00] pharma. Coase, who is an economist at University of Chicago, where things like "markets make good choices" was the theology, was wondering, well, okay, if individual economic actors make good choices, in fact make better choices than centralized entities do, then why the fuck do we have companies? What's going on here? Why do these things show up?

Of course, he said, "Oh, the reason for that is because there's another thing going on called transaction costs, and that market transactions have [00:52:30] higher transaction costs than the transaction costs that sit inside some kind of pre-associated envelope." If you and I agree that we're going to split the returns on our activities 50/50, so we don't have to make any more negotiations past that first negotiation, now we're a partnership, and we can now both just throw it into making that thing work very quickly. We don't have to rethink about it. We just are very creative at the edge; whereas, if every single time either one of us does something, we're [00:53:00] constantly having to renegotiate some kind of transaction, the cost of negotiation, and by the way the cost of monitoring and the cost of interpreting and enforcing, goes through the roof.

What ends up happening is the market collapses into a series of firms that are defined by a boundary where, on the inside of the boundary, you've got a whole bunch of agreements that solve the transaction cost problem, and a lot of people to coordinate in a very high velocity, [00:53:30] low cost way. Then, those firms then do the market transactions back and forth between each other. Now, that obviously works. It built the 20th century and even earlier, but it runs into boundary condition problems, where, for example, information inside one of these envelopes can't easily translate and connect to the information outside one of these envelopes.

For example, let's say you had Apple and Google. Inside Apple there were three engineers who had developed something [00:54:00] really interesting and important, and inside Google there were three engineers who developed something really interesting and important. In both cases, the missing piece was the opposite innovation, where if they're able to connect those dots something 100 times more powerful would emerge, but because they're inside those envelopes, not only is there no obvious way to make that connection happen, it's in fact actively inhibited, in fact possibly even illegal for them to cross those boundaries. This is the point.

In the blockchain environment, we may [00:54:30] be in a circumstance where, through automation of contracts, smart contracts — say, if we're in Ethereum — we can radically reduce transaction costs by maybe a factor of 1000 and, as a consequence, collapse most of the economic utility associated with large-scale and long-enduring firms and therefore get a whole lot more of the surface area, this innovation, exposed to a broader shareable environment and, by the way, also do it in [00:55:00] a way that enables, as you said earlier, sharing to make sense, meaning, on the one hand, recordkeeping is better. The innovators themselves are able to have high confidence that their value will actually loop back and connect. On the other hand, you have ways of wiring and incentive structures who could do things like actually consider the commons as a commons and build into code rather than build into, say, norms or law, ways of enforcing the commons against strategies of the commons [00:55:30] and things like that.

Daniel:There's a few companies that are working on trying to make some ride sharing program like Uber on a blockchain, so that you decentralize the central company, the Uber or the Lyft, as a company, which is going to be extracting a lot of profit from the system, driving the price of the transport up for everybody, or the amount that the drivers can get paid down, and so if you were to decentralize that, you'd have a scenario where it would be more value to everyone with less central [00:56:00] extraction. Then you say, "Well, we still have to be able to pay for the thing." Well, that's where an ICO or something comes in that you can pay for it without needing a 1000X return on an initial venture capital, financial service type thing.

Jordan G.:Mm-hmm (affirmative).

Daniel:That could be done with pharma. Obviously, there's a lot of science to do to develop a new drug and/or develop a new surgery or develop a new diagnostic procedure. There's real cost that's involved, but the real cost that's involved [00:56:30] doesn't end up equaling the total cost of the thing afterwards, because of all of the profit that that central company has to make and the financial services that are involved.

Jordan G.:I mean, you can ... Actually, the economics are pretty easy. Retail is carrying the full burden. I mean, at the end of the day, the consumer is carrying the entire burden of the entire supply chain, including investors, and so, to the degree to which you can empower the consumer to create the capital structure that generates the innovation they're ultimately consuming, either [00:57:00] they show up as the investor, in which case they just get the return of their own consumption, or prices go down. Either one is sort of equivalent and probably in between, because some consumers will not have been capital providers.

Right now, for example, in the one we were talking about, hospitals carry most of the retail cost of providing medical care, and so they already have plenty of money. I mean, they're pouring lots of dough into pharma, so this just becomes a way for them to reduce the amount of money they're putting [00:57:30] into something they're already spending. Just basically, it shows up as spending less money more effectively, which, if anything, any of the stories that we tell about capitalism are even vaguely true, then they should be doing that. If you can spend less money to be more effective, that is what you should do.

Daniel:Now, there are a heap of conditions that we don't yet have good drugs developed for, because there is no profitable way to develop them. The cost that it's going to take, because there's either not enough people that have that disease or because rather than treating a symptom forever, we'd be curing something, and [00:58:00] we just can't charge enough for a one-time treatment to make back the billion or half a billion it costs to go through phase three clinical trials in the current landscape, et cetera. If we bring the cost of actually being able to produce it down, we also open up a now profitable market to work on discovery of heaps of solutions that currently just don't get researched.

Jordan G.:Sure, well, I think it goes down to the notion of ... Oh, cool, can I ... I'm going to pivot this a little bit.


Jordan G.:[00:58:30] What I'm going to do is I'm going to shift the language and shift it from scarcity to abundance, and in abundance, I actually want to talk about two things. The first is what we've been largely talking about, which is what is the economics of abundance? I think it's a very nice conceptual model to say that almost all, I mean, almost to the limit of all of the thinking about economics that has been done thus far has been scarcity economics. We're right now in the process of the obsolescence of that entire approach, [00:59:00] which I'm going to get to in a second, but this begs the question, okay, well what does abundance economics look like, which has to do with things like, okay, well, how do I appropriately incentivize innovative people to create solutions to gigantic problems, but where scarcity, and therefore profit based upon scarcity, is not available as the right solution? This is categorically what you just articulated.

Daniel:Specifically, when you make money, or [00:59:30] incentive of any kind, solving a problem, the perverse incentive there, the scarcity-based incentive, can be that you're now invested in that problem ongoing, so that you manage it, right? The military-industrial complex, the [crosstalk 00:59:42] complex-

Jordan G.:Right.

Daniel:As opposed to how do we actually, then, get to the abundant side of make money, just obsoleting the problem rather than ongoingly managing it?

Jordan G.:Yeah, in fact, you can even make it like how having the highest leverage on increasing collective wellbeing would be [01:00:00] the thing that you're looking to accomplish.


Jordan G.:Which of course, if you would imagine taking the most innovative people and just fully empowering them to focus on that problem, that question, could you imagine how much more effective we would be? I can't even, probably 100 times more effective almost immediately, within weeks actually of, if you could just pivot that direction. In that context, I [01:00:30] want to explore a little bit of the branch to the right, and then maybe we can come back to this branch here if we'd like, which has to do with the other side of abundance. This is something that I was just talking about with some folks yesterday, so it's top of mind, and that has to do with everybody being obsolete, or most people being obsolete.

What I mean by that is absolutely not that people are obsolete, obviously not. What I mean is that the stuff that people have been doing to keep themselves busy goes away. [01:01:00] What's interesting about that is that, because of a lot of the characteristics of how we've gone about meeting our needs and how we've been trained to be valuable and useful in Game A, we are actually quite addicted to being busy, which is the problem, all right? That's actually the issue of abundance.

This is why, for example, a universal basic income is simultaneously a good idea and a terrible idea. On the good idea front, at least it makes sure that people don't starve to death [01:01:30] before we figure out a way to do something differently, and that's useful. On the bad idea front, a whole bunch of people addicted to being busy, who can no longer be busy, is in fact a moral, ethical, and ultimately actually political and physical disaster. This actually ends up being one of the core problems that needs to be addressed and thought through and experimented with and then delivered on, which is how do we, rather rapidly actually, [01:02:00] train people to kick their addiction to being busy and relearn the capacity to actually engage with the world and with life authentically, and without any necessity of being busy at all? It seems like an odd thing to be an emergency crisis, but I believe actually that's the emergency crisis, and it'll turn out that one of the biggest economic markets in the era of technological [01:02:30] unemployment is going to be helping people relearn how to meet their needs and be fulfilled, without being busy.

Daniel:Mm-hmm (affirmative), okay. All right, you're bringing up the topic of technological automation, the emerging technological automation with robotics, with AI, et cetera, [01:03:00] obsoleting a huge amount of jobs and saying people are currently addicted to being busy. Other ways that people have said that and could identify with it is people have their identities wrapped up in what they do to make money, and that a lot of fathers have their identity wrapped up in being a provider in a particular way, and the particular craft that they came from, or whatever. Now that we're going to relate this back [01:03:30] to ... You were saying that Game A optimized people for filling a fairly narrow niche and didn't really care about the rest of their wellbeing, and that narrow niche was well filled by them staying busy doing that thing.

Jordan G.:Mm-hmm (affirmative).

Daniel:Then they, of course, have not learned how to ... and that education was coupled to that. Education worked on making them good at identifying with being that narrow niche fulfiller, right?

Jordan G.:Mm-hmm (affirmative).

Daniel:I am a lawyer. I am a doctor. I am a marketer. I'm a whatever, right? As the [01:04:00] macroeconomy shifts, and economy and education are bound together in this way, because the economy is the environment that people are having to be prepared for by the educational system, so if we get something like universal basic income or a commonwealth system based on access or something like that based on a way of having technological automation not just create a total failed capitalist state, this obviously requires a totally new type [01:04:30] of education, and you're saying how do we have people not get ... heal their addiction to being busy. This is really now again where we're talking about the intersection of personal development, the thing we call education, vocational development, purpose, medicine, which is how do we create whole, healthy beings. You mentioned the term sovereignty, which is core.

If you would ... You were the first person that taught me about the history of the U.S. education system, [01:05:00] and how it specifically evolved to make beings that were well designed for the industrial revolution era. I think that's a valuable piece of history here, if you don't mind sharing it, and then go into, from that, what would the future of education look like that would address this topic that you're bringing up, also, the future of really supporting the types of whole human process needed, so [01:05:30] education and wellbeing support, and sovereignty support?

Jordan G.:Okay, great, so if I lose track, just remind me there's a third piece to this move. I'm going to just start out with the first, which, well, okay ... back in the 19th century, when we were trying to really start to formalize the approach that we were going to be engaging in education, there were ... Well, let me back up. There are in fact many, many ways to do education. That's the first. There's actually many ways.

[01:06:00] When America was beginning to look closely at how we were going to do it, there were at least two major models that existed that had people who thought they were good ideas and had been around for a while, had been very effective. There were actually many more, but there were at least two that were under consideration. One, which is ultimately the one that we actually adopted, was the German model. The characteristics of this model are the ones that we Americans at least are all familiar with, which is the notion that there is a subject matter area, say [01:06:30] math. There is a person, who is the designated authoritative expert, known as the teach or the professor. Their job is to convey the lessons, the content. Everybody else is in the role of being a receiver of information, the student, whose job is to learn that information. Then, the teacher also has the job of demonstrating information transfer or competency in the subject matter by creating various forms of [01:07:00] tests, implementing those tests, and then iterating on that process, right? It's all closed.

What ends up happening is that a student will have some number of teachers, all more or less identical in terms of that architecture, differentiated only by the content, the subject matter, that they're conveying. Then, at the output of that, you will have a set of evaluations, which will say how well you did on the tests, indicating how capable you are in the underlying subject [01:07:30] matter. Notably, what this ends up doing is this creates a giant question mark. Well, this creates a whole bunch of effects, but one of the effects it has is a giant question mark about the degree to which a particular score matters, because who knows how good the underlying teacher or professor was at, A, teaching, or, B, testing?

Maybe I have an A from small college X, and I've got a C from super famous university Y. [01:08:00] It may very well be that my C is in some sense worth more than my A, because the professor in C was better, had more to tell, more insight, and had tested harder. Being average in that domain is going to be much, much better than being "exemplary" in another domain. This is a known issue in the German model. There are lots of other known issues.

Then the other model that existed at the same time and exists to this day is the Oxford-Cambridge model of England, which operates very differently. In that environment, [01:08:30] first the student is principally responsible for, in fact, consuming information, all right? The student does a lot of reading, and they do interviewing and learning the subject matter. They then have a tutor, who has domain expertise, who understands the subject matter and interacts with the student to help the student puzzle through certain problems, points them in different directions, maybe helps them think more clearly about where they're getting turned [01:09:00] around, but the tutor is not responsible for conveying the information, per se — that's the student's job — and the tutor is not responsible for evaluating the quality of the student's work. That's a completely separate function where you actually have an impaneled group, who crafts generalized tests that are given to everybody in a particular subject matter. Many different impaneled groups tend to be responsible for it.

Then, what ends up happening is that if I have an A or the equivalent of an A in math [01:09:30] across the entire set of universities that participate in the Oxford-Cambridge model. Then I should be at A standard, no matter which university I went to. A very, very big university might have more people who show up at A, but if I go to a small Podunk college, and I still have an A, then I'm considered to be a peer to them in capability.

Now, the reason by this is interesting ... By the way, there [inaudible 01:09:56] a third, which is the guild model. In the guild model, you actually have even a [01:10:00] different approach, and this is because in the guild model you're largely trying to convey things that actually can't be well done through information transfer. They're more associated with complex skills practices, classically things like, say, carpentry or medicine, and that's actually pretty guild-y, where the apprentice associates with somebody who's quite skilled in the art. The person, who's skilled in the art, the master, gives them tasks that are designed to be [01:10:30] at their level of capability, but by virtue of doing them, they increase their level of capability, and the master basically just puts them on a path of more and more and more complex tasks. The individual student, just by doing stuff and every once in a while interventions and hints and notes and provocations, builds their underlying capacity, until they themselves have enough capacity to leave and go off and take a whole program.

By the way, there are many, many other approaches. That's the history. The history is that we, as Americans locked into a particular [01:11:00] model and then have, using our earlier language, the basin of attraction now is completely locked in, meaning that ... I actually remember very clearly, when I was in first grade, the teacher was telling us that we had to work really hard on this particular piece, because, I tell you what, second grade is no joke, much harder. If you want to do well in second grade, you've got to do well now. Of course, there's just a handoff. If you want to do well in fifth grade, you've got to get your shit together in fourth grade. If you want to do ... All the way up until finally, well, why am I doing this at all? Well, if you want to get a good job, the handoff from [01:11:30] the education vertical to the work vertical.

Now, a couple of things come out. One, that entire model was already linked to the notion of getting a job or getting a good job or being qualified for a particular job. Then, remember this is true just through high school and even vocational school, with college being added on after World War II, and as the economy moved more and more into a domain where information processing capability and credentialization became minimum requirements for having "a good job" [01:12:00] in the economy.

It's reasonably good at conveying ... What is it called in France? Is it rote, I think? It's reasonably good for conveying rote information. People who process through that model will end up doing a pretty good job at crank turning. Give me an input, where I have actually learned a particular process to process that input, and I will give you, with pretty high predictability, a predictable output, which maps pretty closely to industrial civilization, right? The idea was [01:12:30] the education system and the economic system of that era were unsurprisingly similar to each other.

Daniel:If I had an early industrial revolution with the types of production lines where I just needed people to be able to do a certain job that needed to be fully fungible, I could remove someone from that job and put someone else in, and I needed X number of people on the assembly line to do that thing, and then if they [01:13:00] were off the assembly line, and they were a bookkeeper, I needed to know, okay, this person can do this function called bookkeeping, so I could make an org chart and make a firm, then in that environment, we're basically using people like we're making robots to do now, using them for a very specific, defined process function, so then the goal is make them a good robot.

Jordan G.:Yeah, and I think this is probably the best way of grasping it. In any kind of thing that you're doing that has similar characteristics over and over again, [01:13:30] you're always learning everything about it. Your learning system doesn't know what it's learning. It's just grabbing patterns and learning how to adapt to those patterns, so if you're going to kindergarten, all the way up to, let's just make it high school, you're exposed to a wide variety of different kinds of content. You're doing English. You're doing history. You're doing social studies. You're actually exposed to a wide variety of different kinds of personalities. What is exactly the same every single time is this core architecture of broadcast authority and [01:14:00] narrow-focused, receptive student. I mean, that's what you actually learn in this system is that model.

That's the key transfer. It doesn't actually matter whether or not you take the branch to become a biologist or the branch to become an English teacher, because everybody learned how to operate in that disciplinary mode of having somebody who's the boss, who has the magical answers, conveys the authoritative information that my job is to figure out how to [01:14:30] parse what portion is that authoritative information that I'm going to be tested on, and then, when I am tested, pattern recognize what is in fact the valid answer from the information that I've stored, and give it back. That may be, by the way, saying the right thing, just not making the person angry, but whatever it is, it's that power relationship that is actually being taught in that infrastructure, and that is precisely the power relationship that you're looking for in industrial civilization.

It doesn't matter whether you're working on an assembly line, putting caps on bottles, or you're an accountant, [01:15:00] or you're a lawyer. In every one of those domains, even though the information is different, the architecture of how the hierarchy operates is identical. That, I think, is the key thing to think about. I guess the point here is that the output of that is people who, in fact, really rather dramatically lost their sovereignty, really rather dramatically lost their individual capacity to, for example, create their own identity, willy-nilly, as they wish, or to respond to life [01:15:30] without having to make use of somebody else's pre-engineered scripts.

Daniel:I don't know if you ever saw it. There was a paper Alfred North Whitehead wrote on the problem of hyperspecialization, that was speaking to this model. It was meaningful to me. He said the kids that seem smart or more talented, we push them into specialization younger, and then we push them further and further into specialization, so by the time they finish their PhD, it is on the most narrow subfield of molecular biology or string theory that only [01:16:00] a few other people in the world know, and so none of the people that have a lot of cognitive horsepower are ever looking at the whole, which, if the whole wants to not be disturbed, you would try and make it do that, right?

You would make them very sharp gears inside the machine, but not something that was looking at redesigning the machine as a whole. Then, the people who are left to actually look at the whole and what's wrong with it, in externality, are people that didn't do that well in the system as a whole. Now, we're in a world where [01:16:30] we have to actually redesign the entire system, the whole game, and that requires a different set of thinking than how to optimize some tiny part of it.

Jordan G.:Yeah, and this is true in both directions, meaning that everybody has to actually shift, although I guess, to be sure, there is differential value to different people that are shifted to different capacities. There's the more you can get people who have been [01:17:00] selected for high cognitive horsepower to have, for example, more awareness of the whole, more, say, a broader scope of empathy or a better sense of how externalities actually work, one, the more they'll be able to play together. They'll be able to collaborate with each other, which radically increases their capabilities. Then, two, the less likely they are to use that cognitive horsepower for bad ends, because they'll just be aware of it. They'll notice it themselves, and then they'll [01:17:30] engineer around it.

Daniel:Okay, so now you're talking about that these people who are actually ... that the education system was actually optimizing for deferring to authority and for being part of an authoritarian structure. Even if you're an authority within it, you're also still subordinate to other authorities. That's the whole deal, and that people lost their sovereignty. Now, we're saying, if you want to take the people with high intellectual capacity [01:18:00] and make them really sovereign, they need things like empathy and the ability to work with other people. Would you define sovereignty?

Jordan G.:Yeah, I think that's something we've used quite a bit, and we need to actually be pretty clear about what we mean, because first, if you happen to be doing this from a very old school American history, we don't mean the same thing, I think, that Jefferson meant. If you're sitting around in the contemporary environment, we definitely don't mean the same thing that, I think, the [01:18:30] freemen movement means. It's a term of art, actually, but it's such a powerful concept that I think we want to get a good definition and get that definition out into the world.

The basic proposition is that sovereignty represents your capacity to be an effective agent in the world. Of course, what does that mean? If you think about what it means to be an agent in the world, that has to do with, on the one hand, your ability [01:19:00] to have accurate perceptions of what's going on in the world. If you can't perceive what's happening, you can't make good choices, and you can't respond very effectively. Then, second, your ability to make sense of those perceptions. If you're overwhelmed by too much input or you don't have the right framework to take the information that you see ... Let's just say, for example, the problem of the tsunami back in Phuket, where people could see [01:19:30] — they could visibly see — that the sea had receded, but they couldn't make sense of what was going on, so they couldn't then make good choices.

Then, third is then the ability to take the ability to make sense of what's going on, and then take a look at, then, what you could do, the kinds of actions you could take, and connect those two together into making good choices, the choices that are most likely to simultaneously deliver on the results that you desire and the least amount of negative consequences and the least amount of externalities, [01:20:00] with the least amount of effort. Then, the last piece is, in fact, the actuation piece, which is then the execution on those choices, so that they actually do deliver the results you intend, with the least amount of unintended consequences, and with the least amount of effort. That whole, that entire construct, is what we're defining as sovereignty.

What's important is to actually recognize there's almost a spherical geometry to this thing, meaning that if you're overbalanced in any one of these characteristics, that lack [01:20:30] of balance ... You could think about it like it takes the sphere out of round. You might actually have, say, a wheel that's got a dent in it, and so, as it's rolling, it keeps flopping. This might be, for example, somebody who lacks the ability to make sense of — let's pick a very simple example — other people's facial expressions. I can see that your face is doing stuff, but I can't make sense of it, so now what ends up happening is that my capacity to take information from my environment, convert it into meaning, and make good choices has got a big blind spot, which is going to show [01:21:00] up, for example, in me making weird choices around other people's behavior, because I can't actually read their faces. That's a simple example, lots and lots of examples.

Again, obviously, if you can't hear, then I can't make choices based upon the sounds of my environment. You can do it on any of the dimensions. The point is that there's actually a very interesting notion of the sphere as being the appropriate shape. What you want to do is you want to take a look at somebody and make sure that they're in round, that their sphere is as round as it can be. Then, you can start thinking about how to expand that sphere. [01:21:30] This actually loops us back all the way to the beginning.

Remember, we talked about how complex systems have all kinds of different dynamics that it's feeding back on each other. If you pull one piece, it will tend to get pulled back into what is the basin of attraction. The same thing is happening here with a human being and their capacity. You've got all these different elements that are very tightly wound into how you're able to show up in the world, and there's only so much I can do to increase, for example, your cognitive intellect, if I don't also increase your ability to perceive the world, or I don't also increase [01:22:00] your ability to act in the world.

One of the interesting things that happens to contemporary humans is that we have a massively increased individual capacity to perceive all this information flowing in from the information environment, but our ability to act is actually minuscule in comparison to our ability to perceive. We can see that there are terrible things going on all over the world, but we can't do anything about it. Our response, then, is to feel preemptively defeated or preemptively cynical, or various things. We've got a [01:22:30] fantasy notion of what it would be to be powerful, all kinds of various motives like that, which aren't, in fact, capacity increasing.

Then, conversely, human beings as a species has an enormous actuation capacity. We can blow shit up like crazy, but our sense making and choice making capacity is rather minuscule in comparison to our collective actuation capacity. We can talk about this fractally. Individual human beings — in fact probably even at a lower level, individual human systems — individual human being [01:23:00] have this sovereignty, which ideally is in some kind of well-balanced smooth round and then can be increased as an individual, and then individuals cluster into groups, and these different groups have the same dynamics. You can imagine, for example, when you have a brand new basketball team of five people, who maybe they're all relatively skilled players, but they had never played together as a team. Their team sovereignty is all wacky and can't actually get things done, but as that team practices and practices and starts to get real [01:23:30] fluid with each other, its perception, sense making, choice making, and actuation elements begin to flow through nicely, and then you actually have a sovereignty as a team that begins to increase. The same things happens as you scale all the way up. Okay, that's a lot.

Daniel:Okay, so I want to restate the essential points really clearly and make sure everyone got them. Sovereignty made up of three things, and the reason you're saying a sphere is you're saying that these three things are the three axes that would make up a three-dimensional [01:24:00] shape like a sphere, so that they ... That means they're orthogonal to each other. They actually represent the vector space of being a human, of sovereignty. You said, sensory input, information processing of that sensory input to inform a choice, and then actually acting, actuator output, and that there's a closed loop, because then you act in the world, and you can, in turn, sense the effects of the action, and then make sense of it, and act again, and so you have this closed loop, and that we have [01:24:30] just words that we've used before, and we use,

This is actually related to the mission statement of Neurohacker, of sovereignty increasing, this definition of sovereignty, that we can think of the sensory part of it, the first part of it, as related to sentience, the ability to actually have not just the information that's coming in, but that it's landing in a being that's recognizing it and experiencing it. The second part, the ability to take all of that, the internal sensing, [01:25:00] our own feelings, our proprioception, our past awareness in learning, plus what's happening in the world around us, from our eyes and ears and information and make sense of it is intelligence. Then, agency is our ability to then act on that in the world, especially act in the presence of pressures that might make it hard to act, increasing agent incapacity.

Jordan G.:Mm-hmm (affirmative), yeah.

Daniel:The triplicate of sentience, intelligence, and agency makes up this sphere.

Jordan G.:[01:25:30] Right.

Daniel:Now, if someone has very high agency, meaning they're very motivated, they have a lot of resilience, but they're actually not making good sense of the world, they're going to make a lot of very powerful, very bad choices.

Jordan G.:Mm-hmm (affirmative).

Daniel:If someone is actually sensing the world well and very intelligent, but has low agency, then they're going to have a lot of good ideas and be crippled to make them happen, right?

Jordan G.:Mm-hmm (affirmative).

Daniel:We can look at any of the combinations of these and say only all three ends up actually being adaptive.

Jordan G.:[01:26:00] Right. Now, we should be careful. Under certain circumstances an out-of-round is right. We talked about, for example, if you're a fighter pilot in the middle of a dogfight, big chunks of sensory capacity and sense making need to be not input. I mean, you actually need to have a different shape than in round. This is actually ... I mean, we could do the whole complicated complex thing, as well, that being in a pure, at a high [01:26:30] quality sphere is maximally adaptive under uncertain conditions, meaning in environments where what the future's going to look like is not exactly the same as it looks right now. Then, in that case, it is for sure the case that a sphere is the best geometry.

Daniel:I think one way of saying it would be ... The fighter pilot obviously has to be intaking information, making sense of that information, and acting on it, but the information about how much [01:27:00] they need to go to the bathroom and lots of other things, they need to really suppress and hyper pay attention to their visual cues and their whatever, right?

Jordan G.:Right.

Daniel:The adaptive capacity to be able to pay attention to the right information and to not pay attention to the wrong information, because then, when that same person is making love or tending to a baby, it's different things they need to pay attention to with their limited bandwidth, so we could say-

Jordan G.:Right, and this is, this is actually-

Daniel:It's always round. It's just different rounds, based on the environment.

Jordan G.:[01:27:30] Yeah, well, again, because it's state switching between domains is the problem. What happens in the Game A is that training will build whatever your roundness is in a given domain, but you don't have the individual agency, the individual capacity to do your own kind of state switching and your own designing of your own sovereignty in a given domain-


Jordan G.:So what you end up having is ... Go ahead.

Daniel:Most of the fighter pilots and other people highly trained in military coming back after the war and being really maladapted [01:28:00] to a non-war environment.

Jordan G.:Right, exactly, so then they've been pushed by external, extrinsic factors, into a particular subspecialization of what is in fact very high quality sovereignty in a very specific domain, but at the cost of their, in fact, actual intrinsic, we might call it, human sovereignty. I guess that's the point. It's a really good example. All of us, in some sense, have PTSD. All of us, in some very important sense, have actually undergone that process of losing our intrinsic human sovereignty to become [01:28:30] who we want to be and in any kind of context and have become, to a greater or lesser extent, very specialized in having been separated from our core capacity.

Daniel:What does education for sovereign beings look like?

Jordan G.:Yeah, so this was actually the third thing that I wanted to talk about on the education arc is that it's interesting, actually, I think quite lucky, that we're actually coming into this problem from two [01:29:00] distinct directions. One direction is what happens to the educational model, the German model, in a pace of accelerating change. What I mean by that is in a pace where, for example, having asymmetric information becomes less and less true. Having access to information becomes more and more of a commodity, all right? Does it really matter at all if I ... This is actually a really good example. I remember this when I was in high school.

There was a time when knowing [01:29:30] the multiplication tables in your head was extremely useful. Now is not that time. If I am separated from a device that can calculate long division, I've actually got bigger problems than my inability to calculate long division. That's no longer a functional capacity. It doesn't matter, all right? I can just import that capacity through some kind of tool and do it a hell of a lot better than I could ever have done it by spending countless hours learning how to do it internally. That's just too generic. Think about driving around. Not only is being [01:30:00] able to read a map becoming an obsolete skill, but soon driving at all is going to be an obsolete skill, et cetera, et cetera, et cetera.

The output, the thing for which this authoritarian training regime was ever useful, which was putting specialized knowledge into the hands of specialized people, who could operate within a higher framework, that entire thing is becoming obsolete at light speed. One side of the equation is, okay, well shit, if we want to go through the basic art of, call it, retraining [01:30:30] or educating anyone to be adaptive to the future environment, what we have to do is we have to unwind a lot of that and think about, okay, well, you're going to be in not 10 careers in your lifetime, but 10,000 careers in the next day, all right, something like that, where the only possible approach is to maximize your individual sovereignty, your individual capacity for where you are, to perceive where you are and what is needful now, and if, by the way, it turns out that you don't have the capacity to address what's needful now, [01:31:00] how to build that capacity.

Learning about how to learn and learning about how to have the stick-with-it-ness to be able to commit to doing what you have to learn, learning how to have emotional resilience to deal with circumstances where you're overwhelmed by your environment, really deep, fundamental, core capacities that are completely absent from education as we currently know it, or if they are learned, they're learned willy-nilly, and are [01:31:30] fundamentally applicable under any possible circumstance, all right? Then, what ends up happening is you have a sovereign being, who then shows up at a given domain, rapidly pulls together the specific domain, specific skills they need to have, maybe even subspecializes, but never becomes the subspecialty, always maintains the integrity of their core sovereignty.

Daniel:This was a key thing. Never becomes it means something at an identity level.

Jordan G.:Yes, that's right. I am not a fighter pilot. I fly fighters, sometimes.

Daniel:[01:32:00] Yeah.

Jordan G.:I'm not a fireman. I'm not a banker. I'm not X, Y, or Z. That's something that I do sometimes. It's a game that I play, right? It's moving into a state where you are not the games you play. You play games, but you are not the games you play.

Daniel:Now, this was also key that, for most people in Game A, Game A is already defined. If you go play most games, you go play soccer or Monopoly, the rules are already set, and the question is can you get [01:32:30] good at doing it?

Jordan G.:Right.

Daniel:When you're learning subjects in school, the answers are already set. There's clear right and wrong. Can you do a good job at getting that right? Then, when you go work at a company, it's the same thing, right? Someone else is setting the objectives of the company, and so you mostly have to have a very little bit of sovereignty within whatever domain space isn't fully specified, but towards a goal that someone else set.

Jordan G.:Mm-hmm (affirmative).

Daniel:You don't have to self-assess what needs done and how to go about doing it. You have to get trained [01:33:00] in a very specific capacity and do that. Most people who've been trained that way, so intensely, the idea of assessing what needs done and how to go about doing it without someone else telling them how to do it is overwhelming.

Jordan G.:Yeah, it's really challenging. I think this is showing up more and more and more. That's going to show up particularly heavily on the other side of the coin, which is the people who are in fact obsoleted, or their identity, their skills, the thing that keeps them busy, is rendered obsolete, because in that case, [01:33:30] they are going to feel overwhelmed in a lot of different dimensions, and it is, in fact, simply the case that they're going to need to learn how to come back and begin to self-assess, because the notion that we're going to be able to programmatically tell everybody what to do is, one, not very reasonable, and, two, terrible if we could pull it off.

What ends up happening is we have to find a way to, en masse, rebuild that core kernel, which is, okay, reclaim your sovereignty, reclaim your ability to make the choices that are your responsibility [01:34:00] to make and take ownership for the consequences of those choices back out in the world, which, as it turns out, by the way, in terms of just games, is actually where fun lives. It's a very common experience among people who play, say, video games, computer games, that any game where you're playing against a machine, which is to say, where the game is ultimately finite, it has a very specific curve to it, where, when you're first [01:34:30] in it, it actually feels really fun, because you're exploring where it actually kind of feels real.

After some little bit, you begin to actually understand where it's not real and begin to optimize for the game aspects. Then you actually have an accelerating arc, have a visceral response, because now you're winning. You can actually win the game. No longer are you playing the game, you're now winning the game, but at a certain point, you've become so good at winning the game that you no longer actually get any kind of visceral feedback from winning the game. It's no longer [01:35:00] interesting, because you've now gamed the game, and achieving certain kinds of characteristics, like getting scores, becomes diminishing returns.

This, by the way, is true of any finite domain, right? When you first enter into the finite domain, the act of exploring is really interesting and fulfilling. Then you've optimized. You've found out what the shape of the domain is and what kinds of things work and what don't work. Then the act of optimizing has a visceral response, because that's where the rewards come, but if you become that thing that's optimizing, then [01:35:30] you're now locked into a circumstance where, at some point, you're going to be over the top of the curve, and now you're getting diminishing returns. Of course, the point is that if you become that thing, you've actually lost the ability to move out and jump into other kinds of games willy-nilly or play games that don't have those characteristics at all.

Daniel:When we think about optimizing humans for sovereignty, so that they could move between doing [01:36:00] fighter pilot or making love or raising a baby or assessing a totally foreign environment or whatever, there's obviously education that's involved, and you also started, in terms of how to learn new skills, right? There's meta-education. There's epistemology. How do I assess when I need a new skill? How do I go about learning new skills well? There's all of that, but you also said one has to be able to deal with the emotions that arise in new environments, so there's emotional skills and personal skills. Then, [01:36:30] we also related the topic of medicine and health care to this, in that we've moved from just a sick care model to a sovereignty optimization where people's physiology in their state and their ability to address it is also part of that.

Obviously with Neurohacker, we're starting to look at mind-brain, right? There's a goal there. We talked earlier about how things like economics and macro world things affect people's health through [01:37:00] advertising dynamics that are sending the hypernormal stimuli of sugar all the time, through marketing, but then there's this other side of do people's physical health, wellbeing, affect macrodynamics, and if so how, and how is that part of the sovereignty optimization?

Jordan G.:I'm sorry. I didn't understand that. Ask that again?


Jordan G.:You mean, along the lines of does the population where everybody in the population is depressed show up, [01:37:30] for example, in different politics?


Jordan G.:Okay.

Daniel:Different consumption patterns, crime patterns, whatever.

Jordan G.:Right, I mean, obviously the way that I asked that question makes it pretty easy to answer. The answer's obviously yes. It's funny. We can do it all the way down. Let's say, for example, you're somebody who has a particularly addictive response to anxiety, where you [01:38:00] eat food because the visceral act of eating of food causes your body to have certain dumps of endorphins and serotonin levels go up, and so, therefore, your anxiety levels ambiently feel like they go down, and so you, more or less, feel like you're back into being okay.

Then you're going to have the characteristic of overeating. Well, interestingly enough, if lots and lots of people have that characteristic, then you're going to have an economy that is going to begin to optimize for those kinds of choices, which is bizarre. You have a both. You have a feedback loop.

[01:38:30] On the one hand, people who have an addiction to that particular approach to dealing with anxiety are actually generating a real economic signal of I want more things that are subject to overeating and, therefore, the food artifacts that do actually satisfy that addiction well, like say potato chips. On the other side, you have a manipulation media and advertising infrastructure that is incentivized to push people into domains that are likely to be triggered by that particular addictive response, because that will maximize their ability [01:39:00] to generate profits on the products they've already spent time investing in. That's a really bad feedback loop.

Then you can imagine. Say, for example, you're somebody who's in the industry, and you're present to the reality of this feedback loop. Then, you're going to have to be engaging in your own personal adaptive response, which some people call as if sociopathy, meaning that if you're present to the negative consequences of the choice that you were locally responsible for, you either have to choose to be delusional, which is to say to not take your [01:39:30] own responsibility seriously and imagine something which isn't reality; suicidal, meaning you have to actually make choices that you think are in fact good for the whole, but are definitely not good for you locally; or a sociopath, meaning you have to be willing to accept the fact that consequences of your choices are good for you, but not good for the whole, any one of which is, in fact, a terrible thing. What's interesting is that no given individual agent, acting on their own, is likely going to be able to resolve that problem.

Daniel:The game dynamics are if you do the thing [01:40:00] that's good for the whole and bad for you, you lose, and so then-

Jordan G.:Over time, iteratively, there are fewer and fewer people who choose that-

Daniel:And more and more people who choose either the as if sociopathy or the lie.

Jordan G.:That's right. Yeah, and so what ends up happening now, if you imagine that at a neurological level, you spend, let's say 10 hours a day in a space where you're combining a variation on as if sociopathy and delusion, you're actually going to have congenital neurological changes, which are going to show up in [01:40:30] all of the rest of the ways that you show up in life. You're going to have a weird relationship with your spouse. You're going to have a weird relationship with your kids. You're going to make weird choices in politics. I mean, it's just going to continue to go, which is not that different than saying, for example, if you had an entire population that was addicted to opium or an entire population that was functionally alcoholic, which, by the way, Medieval Europe could be characterized as an entire population who were functionally alcoholic. I think, pre-mid 19th century, [01:41:00] giant parts of America had that same characteristic.

We can run this at a neuro, at a physiological level. We can run it at a behavioral level. We can run it at the feedback loops between them, but it's important to take into account the fact that that's the case, and then think about what kind of levers ... Again, we keep coming back to the same notion of when you see the whole, you see how all the pieces feed back on each other, it is in fact just necessary just to be thoughtful on how they feed back on each other, and how does one begin to engage in this [01:41:30] subtle process, which I don't think, by the way, is actually intrinsically harder than other things that we do well. It's just not something we've actually developed a lot of skillfulness in yet. I think that the practice of being able to be perceptive of how many, many various systems operate and being able to be skillful in shifting them in desired ways is actually just something that we need to build skill at. I don't think it's something that is obviously beyond our capacities.

Daniel:Okay, so I want to restate and underline [01:42:00] something that Jordan just said, for everyone listening, because it's so key. He's talking about the feedback loops here, so wait, is it that demand drives supply or is it that supply drives demand? It's very much both, and it's really critical to get that, of course, originally demand drives supply. More people want something, and supply steps up, but then you have a real source of supply and you want to manufacture. You want to protect the demand, because otherwise your business goes out, and maybe manufacture more demand, and that looks like marketing, and that [01:42:30] looks like whatever to create manufactured demand, so supply is driving demand, demand is driving supply, and you can get feedback loops that move in the wrong direction, move in the direction of society, as a whole, getting worse.

Similarly, we have dynamics where this very much just addressed one of the core differences between what the rational left-right argument has largely been about. Do individuals create the whole, so you [01:43:00] want to optimize for the sovereignty of the individuals, or are the individuals affected by the whole, so you want to make good social systems that make good individuals? It's very much both.

Jordan G.:Mm-hmm (affirmative).

Daniel:You want to make good educational systems, good economic systems, that condition better people. You also want to make more sovereign people that lead to better whole systems. When we start thinking about these feedback loops, and the same is true with if someone is in an economic system that's causing certain kinds of stress and certain kinds of behavior, does that affect their brain and their [01:43:30] health? Yes, but if we also are ... does someone's ... What they're doing with their diet and with their physicality that's affecting their brain and health then affect the decisions that they make in the world? Yes, it's very much both, and so mind-brain interface is a classic one, like supply and demand, like individual and collective, and to really get the basins of attraction right, we have to not think about either/or. We have to think about the synergies in the feedback loops.

Jordan G.:Yeah, this reminds me actually ... What [01:44:00] I noticed, and I hadn't expected to be the case, but I noticed that there was a reasonably common misconception coming back from people about Neurohacker, which was because we had specifically focused on the physiological, body-mind, body-brain piece of the equation, that somehow we were also collapsing the entire space down to just that one thing, right?

Daniel:Mm-hmm (affirmative).

Jordan G.:They were saying, "Hey, this is the elixir of all good [01:44:30] things. Just do this, and everything will be okay," when, in point of fact, of course, obviously that can't be the case, that every single component of all behavioral, interpersonal, social, cognitive, and many, many different kinds of biochemical characteristics are all necessary to achieve wellbeing. You have to learn how to eat right. You have to learn how to engage in various kinds of mindfulness and/or physical practices that are appropriate to you to do well. You have to actually have self-awareness to know how to answer the question of what's appropriate to you. I mean, these are all ...

[01:45:00] Actually, I think this creates, frankly, the highest degree of optimism in the context of the scope of the problems we're trying to deal with, which is that the core answers to all the problems end up actually being very similar, meaning that, yep, you want to solve a problem around health, you want to solve a problem around education, you want to solve a problem around economy, you want to solve a problem around war, first and foremost, always, already, bring it all the way back down to core capacities, because you can't respond to any of them unless you have [01:45:30] them, and if you do have them, your ability to respond to all of them basically just becomes fungible. They're, more or less, domain nonspecific.

Then, there was actually something that came to me, as you were describing, as you were talking a few moment ago, a thought in the path that I thought might be very interesting to share. It's stated in evolutionary language. In traditional evolution, you have an organism and you have the landscape or [01:46:00] the ecosystem in which that organism is existing. The basic edge is that the organism is striving to be fit, meaning it had to compete for scarce resources, which may be its own body against predators, and be able to reproduce.

One of the interesting things that exists in an organism's portfolio of actions is a concept called niche production. If you happen to be, let's say, [01:46:30] really, really good at thriving in the swamp, if you had the capacity to turn more of the world into swamp, that's to your local advantage. Of course, it turns out that there's a problem, that if you become so capable of constraining and controlling your environment that you lose your individual adaptive capacity, then, if and when something happens that pushes the environment out of your control, let's say the swamp turns into desert, you're just dead.

There's a very interesting balance between niche construction [01:47:00] and intrinsic adaptive capacity, but there's actually even a higher order of synthesis between those two, which we may actually just be ... we humans may just be uniquely entering into the possibility of perceiving and doing and, in fact, it may actually be necessary that we do it, which is if you can come to the point where you can actually have full responsibility for your individual wellbeing and for the enduring wellbeing of the niche in which you live ... Now, [01:47:30] as an organism, you are no longer evolving in a niche. You and your niche are, in fact, co-evolving, such that the integrity between the two is fully maintained, meaning that your niche does better, the better you do, and you do better, the better your niche does. That has an endurance characteristic that cannot be achieved through any other evolutionary strategy.

Daniel:Mm-hmm (affirmative), yep, and I think that is a great place to leave this [01:48:00] one on, because we have went long here and covered a lot of territory from economics and then cryptoeconomics and blockchain to education, health care, medicine, sovereignty, niche construction versus intrinsic adaptiveness, so I think this will be a fun one for people to figure out how to make show notes of. If anyone wants to see [01:48:30] more of Jordan's thinking on these topics, sometimes he writes on Medium, and it's worth ... just Google Jordan Medium, Jordan Greenhall, and you'll see he's got actually some really epic articles on sense making and politics and sense making applied to different domains like that. Yeah, this was fun. This was good.

Jordan G.:Yeah, it was fun. Thanks, Daniel.

Daniel:All right, thanks. Bye.

Jordan G.:Bye.

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