hello and welcome to the centralized Justice broadcast I'm federicoas I am president at The Cooperative clearance and our guest today is Jason Potts Jason is an economist economic theorist who specializes in problems of economic growth and change he works in areas of economic Evolution technological change economics of Institutions economics of innovation economics of cities and economics of cultural and creative Industries his current research focuses on innovation in the comments and on global Innovation policy and he is also a leading researcher on the economics of blockchains and is currently the director of The blockchain Innovation Hub house at Aramaic University so Jason Welcome to our podcast I'm very happy to have you here thank you very much Frederick I'm very very pleased to be here as well [Music] I mean I'm super happy to to get to speak to you because you do research in lots of topics that I find super interesting I mean uh like institutional ergonomics evolutionary economics I want to understand a bit more about I mean how you got into into I mean this field some so tell me a bit about your intellectual biography how did you I mean what did you study how did you get into into this field and and how did you get to this point in your career yeah so um like I'm I've been working in universities all my life and so I started back in the early 90s during my PhD in economics but I I came out of physics as well my background was actually in nuclear physics and with a sort of minor in evolutionary biology and early 90s means before the internet which means that and before the internet in New Zealand and one of the things that was very very easy to do was to come up with ideas that you thought that no one else knew because you couldn't easily search and find and figure out that other people had already had that same idea so basically I thought I I thought I invented evolutionary economics um and it was that was a fantastic sort of um sort of position to start with doing a PhD and it sort of as it turned out in the course of that it turned out I didn't other people had had that idea long before me but it set me on a path of approaching economics very much from an interdisciplinary perspective where I was very very comfortable just bringing ideas and models from other fields um I sort of had enough math background that I sort of I understood the the maths and economics but also the stuff that economics wasn't using and one of the key insights for me was that there was a lot of fundamental models and theoretical Frameworks particularly in biology and particularly around in Game Theory you know and evolutionary biology that just struck me as they obviously applied to economics and so I sort of went down that path and sort of um developed a lot of thinking around that also picked up a lot of work in complexity Theory um sort of early on back in back when complexity theory in their in the 1990s um sort of Led Out of the Santa Fe institution people like Stu Kaufman and other sort of types of graph theoretic Network theoretic models um they're completely common and obvious now but then there are quite new and and somewhat radical ideas so my big thing was to really take evolutionary population Dynamic modeling sort of selection Theory combine that with network and graph there and complexity Theory and go this is how we should understand technological change but the core idea was that economic systems are fundamentally not made of things they're made of knowledge and when economic systems grow they don't grow and they just get bigger sort of physical sense they grow by becoming more complex and they grow as knowledge evolves and expands so right from the start um I was very tuned to understand economic systems as evolving structures of complex knowledge which meant that um I didn't really I mean and this has sort of been this is this has been the thing the the theme throughout my career is that Technologies evolve and institutions evolve or institutions are Technologies they're social Technologies so you know in the just just to sort of loop immediately back to where we are in situations like clear us you know you're dealing with a court system and institutional system um that's a technology it's a technology made of particular rules about how you arbitrate and written and and construct disputes those disputes themselves are made of contracts which are institutions so it's basically it's a technology Tech stack all the way down and once you sort of see an economy as fundamentally made of not just you know physical Technologies you know Industrial Technologies and then there's all this other stuff over there you know politics and culture and whatever but there's Rock the whole thing is a tech stack but some of those Technologies of Social and behavioral Technologies some are physical technology some are institutional Technologies but economic Dynamics this process of you know this thousand year long process of economic growth and change is all technological um Evolution so that's this this I've been sort of swimming in those Waters and trying to trying to build general models of it trying to find areas of application and I started with a bunch of you know building theoretical models um back in the early 2000s essentially mathematical Frameworks for this then I went into creative Industries and cities and really tried to understand how to apply these these sort of abstract models of of evolving economies as evolving knowledge systems um to particular areas and I got obsessed with with creative Industries um and then um we can sort of dig into that a bit but then at some point I started getting very interested in very very early stage Technologies so I had on my list this was about 10 more than 10 years ago I'm looking at 3D printing and Sport um mountain bike Sports you know sports sports Technologies mostly because these were private audits I was interested in new technologies that were emerging that didn't really have intellectual property or were just sort of communities and you know and this weird thing that I've just been hearing about called you know crypto and so that was his one of several case studies I was doing but quickly got completely obsessed by that and you know eight years later here we are I mean um how did you study something from an evolutionary economics perspective I mean what's the methodology I mean tell us a bit about how this industry study I mean Works um in this field yeah yes that's a good question because the methodology is um the methodologies for um sort of studying Open System Dynamics just by definition have to be different to methodologies when you're studying a closed form model so this was one of the basic insights that comes that evolutionary economics has built upon is that you're by definition studying an open complex evolving system which means that um you have to use simulation Technologies you have to your simulation models you have to try and find ways to build models and then simulate the the the forward Pathways of them because what you're trying to do is to discover um you know um to try and discover how what this state space of the system actually is and what the distributions of that actually look like so um sort of so you know computer modeling by definition numerical simulation has to be a big part of that of that story now if that's the case what that means is that the theory that you're using can't be um purely axiomatic or you know just Theory it has to be based around rules that you're sort of saying that these are the generative rules I think are applying or driving the system so you end up with a modeling framework that is far more about trying to build um rule systems that can simulate possible Futures now that's a very very different approach to um the way in which a lot of you know economics is usually studied which is actually far more closed form modeling approaches so so that's that's the high level answer for that but I think one the the broader answer is um it has to be a multi-disciplinary approach um economic systems are made of and there's physical resources that have to be allocated there's legal Frameworks and systems that are that are providing coordination um there's governance and hierarchical systems and teams of people that are partially social partially cultural partially administrative um and they're also just made of people so you're dealing with behavior and Neuroscience and so on so I mean this is why you know I I sort of I think you know I think economics is a particularly interesting science just simply because it's not actually a true science it just combines a whole lot of other things all meat in that one place it's part sociology it's part legal studies it's part Neuroscience it's part behavioral economics it's part administrative science it's about engineering it's part you know all of this full stack of things that comes together to study a phenomena which is just an incredibly complex phenomenon and I think the only other field that has a similar level of complexity is maybe brain science or Neuroscience um we were just dealing but but that's complex for a different reason that we you know we're at the limits of what we can see into it whereas we can see economic systems we all know we're part of them um but they're these incredibly complex involving systems and I think that's also why I've been just so fascinated with what's been happening in web 3 space and digital economies is that you know from a scientific perspective this is incredible where you know I get to be here as an economist you know and observing in real time one of the great Revolutions in economic history um you know these we've had economies for thousands and thousands of years but they've only really gone through these massive Transformations relatively rarely and one's happening right now and and we can study it from the inside so this this this is my thesis that I think what we're seeing in in World economic history right now is this massive upgrade of the underlying um administrative infrastructure that's going from industrial era modes that go back Millennia um that's being upgraded into a digital system that some parts are being carried over but some parts are completely revolutionary new and again this is sort of why you know the work you're doing at clearos is part of that process it's a massive step change upgrade and the underlying infrastructure of economies and you know of course that's messy um of course it's experimental it's driven by Theory it's driven you know um but what myself and my team we've got an incredible team at blockchain Innovation Hub including including some really fascinating Tech lawyers Mata poblad Aaron Lane and and others in that space But you know why we're excited about this is that we get to study in real time get to observe you know um this process of you know of of large-scale global Revolution and economic systems and who were I mean your intellectual influence is having to get I mean into this place I mean who did you read and who do you suggest I mean people should read in order to get acquainted with this you know with the science of evolutionary economics yeah so I mean the like the classic is Joseph schumpeter so um there's the shampoo it was the 19th or an early 20th century Economist um a contemporary of John Maynard Keynes um who um you know basically modern economics blism too and there was the Keynesian group that sort of said economies are machines we can engineer our way through them and then there was schumpeter who um laid the groundwork for arguing that we should be understanding economic process as an evolutionary process and what that meant was and what he meant by that was that entrepreneurs like um mutations in a system they introduce novelty and then Market systems uh the selection mechanisms that sort of that select upon that novelty and you know so if you think of economic systems as evolving complex systems in that way um is the obvious starting point but one of the key influences probably the the let me let me just point it to um there's there's hundreds but let me point it too um one of them is um Frederick Hayek um and Hayek um a you know he's a um is a very very well-known Economist um but what Hayek did was he he was the first person to really understand markets as computational systems and therefore economic systems is not allocation mechanisms that you sort of plan but as computational systems where markets are effectively a series of institutional rules in those rules um perform distributed computation um on bids and asks and you know all the information all the distributed information in an economy and what they're Computing is a series of prices which then guide behavior and that idea of markets as um distributed computation was a genius level just a radical Insight in mid-century that we're still recovering from we're still trying to many people still haven't fully understood the implications of that but what he basically said was economies are computers and Market mechanisms are the way in which they work which means they are distributed to computers um what are blockchains distributed computers blockchains are the realization of that of that Insight so so Hayek um Hayek is is foundational um as a way of understanding what our economies how do they work um the other person who has usually influenced me is Eleanor Ostrom and Eleanor Ostrom actually started as a as a political scientist but what she was studying was um private governance how groups of people come together and create order or create rule systems to govern their own their own um economic activities whether to coordinate their economic activities and I mean what's interesting about austrum and Hayek is that both of them were studying particular mechanisms Hayek was studying Market mechanisms Australian was studying Commons mechanisms both of them are governance mechanisms what are governance mechanisms they're just systems that govern humans that are made of rules where all of the humans in the system have to agree upon the rules and what is evolutionary economics the story of how those rules evolve and change so it's all part of the same sort of way of doing economics by understanding it as complex evolving rule systems um I mean what was interesting about austrum was her methodology she just said um private governance this in theory this shouldn't work but in practice it seems to work I wonder what's going on so she and her team of of you know postdocs and PhD students just spent decades just studying and recording you know inductively analyzing thousands and thousands of Commons is to try and figure out why some of them worked and some of them didn't and with that she was able to surface um sets of rule systems that seem to work so there it is these seem to be the rule systems that are governing that seem to work in private order governance um yeah an incredible bit of modern social science because that was you know that information had been there for thousands of years no one had figured it out she surfaced it and what it meant was that now we can start to understand how you can design private auto governance systems um you can bind there with Hayek's work without an understanding of why markets work is distributed governance systems and coordination systems um if we're looking for other names I'd throw in Thomas shelling I think is absolutely fascinating um one that maybe no one here has heard of is George Richardson an Oxford Economist of the 1960s information Theory um um I'm a huge fan of Herbert Simon from the 1950s on org Theory so there's lots of sort of classic economists back in the sort of early mid part of the 20th century that did a lot of groundbreaking work but all of their work was pointing in the same direction economies as complex evolving institutional rule systems um that that that's the way we understand what an economy is and how they grow and evolve um and you know in this in the crypto space and blockchain space just all of that is the continuation of their trend you know this is fascinating because I mean if you ask me like what's the most I mean the intellectual that had most influence in you it's higher and in particular it's this use of knowledge in society text you know where he explains about marketing as computation and um and in the first episode of this season of the podcast I interviewed Mark Miller who is a computer scientist the founder of algoric and in the 1970s they were thinking of computing markets from the perspective of of Hayek you know paper how you know the pricing mechanism will work to assign you know Computing resources to where it's needed I mean and it's fascinating how different people are coming to the same type of conclusions in the case of Mark Miller from the point of view of computer science I mean your case is evolutionary you know schumpeter and Hayek I know um react to that baby yeah look um I know Mark um I'm just just to be clear I'm also involved in agoric um oh right and you know that yes say I want to say one of their advices um but Mark is a spectacular genius he's one of one of the great Treasures of our modern era um that I wish more people knew about but the um so the agoric papers that Mark wrote with some of his colleagues um Eric kedro and um I think Bill Tallow was involved in some of them later on but they are that is a classic case of work that is decades before its time um so the the agoric papers were basically the opposite of Hayek where Hayek was trying to understand how Market systems are like computers but the agoric paper system where the agoric systems papers are doing and um if you just if you just Google them agoric papers um Mark Miller you'll find them they're they're incredible pieces of Timeless of Timeless scholarship and thinking but what what the egoic papers do is argue in the opposite direction how computer systems can be like markets and it's the same sort of insight um we've been with Mark and and Bill Tello and a few others we've been sort of thinking of these as Nano economics but the the core idea was that and this was this was Mark's genius was just just to think of computer security that a computer was fundamentally a centralized system with a CPU in the center um sending calls and requests to different sort of modules around it and that's the same mental model of a centrally planned economy where you have a central planner sending messages to to various agents in the economy and do this do this and do that whatever now Central planning doesn't work for the reasons that Hayek pointed out was um just knowledge problem um there's no way that that the central unit can have all of the information because some of it is tested some of it is local there's just lots of reasons that that is an impossible computation to make so essential planning ends up working with very very flawed information sets that's why it always fails at scale works on a very small scale level of a family or a small firm but once you get up to millions of Agents it's just it by definition will fail because it cannot process the information marks Insight um which was the basis for forming agorak along with the um Dean Tribble was to understand that from a security perspective and see that the standards of software architectures um have this notion of a central bit of processing in the middle and then a whole lot of clients around the edges that it sends messages too um yeah now those machines can process the information fast but because you've got one thing doing all of the access controls for everything else that is a security nightmare there's one thing is that is dealing with the security and access for everything so what's what Marx and and and Dean's Insight was was that if you made computer architectures more like markets where they're basically each module or each subroutine is Contracting is is Contracting the specific other ones for access to little packets of information to send around if you make software architectures fully distributed um they are far more robustly secure and natively secure and that sort of insight of how you get markets so then okay so how does how does it how does this module bid for resources answer it uses prices so what their Insight was was that you know both computer architectures and economic systems are both systems for processing distributed information for performing computations and the distributed systems have distributed parallel systems have um a lot more robustness um and Security in the case of computer architectures or adaptiveness and ability to evolve um in the case of Economic architectures and when they're designed as market-like distributed objects now that Insight that notion that you know economies are computers and computers are at market economies um you put that together what if you got a blockchain well I mean I had no idea that you you were close to to Mark I mean and I'm a huge fan and I mean what he did in the 70s was I mean groundbreaking I mean as always you know if you're way ahead of your time it's hard for people to understand what you're talking about but you know all of the ideas that he was working on and trying to do and all that so I mean how did you get into into blockchain since you since you mentioned it what was your your trip in the rabbit hole yeah so um I was doing research on very very early stage Technologies and I wasn't interested so much in blockchain as a technology and you know the the underlying how does this thing work what I was interested in was that where it's it was the almost the sociology of it that it seemed to come from nowhere it didn't you know um so my area is evolutionary economics which really means Innovation at the moments I study new technologies where they come from how they grow and change and one of the sort of basic patterns that you see over and over again is that new technologies are invented in Labs or they're patented and they come from you know universities or corporations or whatever and then there's companies those companies um you know sort of build the technology and and try and develop it and seek Finance for it and you know there's a there's a very you know lots of different Technologies all have the same life cycle except blockchain crypto it just did not fit any of the models so first of all no patents secondly it just appeared on this weird sort of Newsnet Forum in the middle of the night you know anonymously um certainly it didn't come from universities it didn't come from you know corporate research layout didn't cover many of the usual places um and this the I mean what it did was it came from the comets and this idea of um radical new technologies institutional Technologies it wasn't even an industrial technology it was an Institutional technology emerging in this weird institutional space it emerged from The Commons and it grew in the Commons and it has stayed mostly in the comments um that was interesting to me because that's that's that's not the path that we normally see normally it's entrepreneurial Discovery born in a firm grows in markets protected by governments that that sort of industrial Innovation framework is most technologies that that we're all familiar with not this one um so I was just I was just fascinated from a scientific perspective why is it different what's going on there and the more I sort of looked into I mean and that then sort of we went down the rabbit hole on that and it wasn't just me it was myself and I had some fantastic PhD students some of whom are now postdocs working with me now um Trent McDonald and Darcy Allen um they were the ones they were the ones that really sort of led me into it and said look you have to come and look at this this is this is fascinating um very soon then started going to conferences met people at Primavera definitely be um who sort of sort of gave me a sense that you could actually treat this as an academic field so this was back in 20 late 2014 2015 or so we started looking into it and um you know even now it's it's not you know it's a bit academically weird to look at it but back then it was super weird um I was just saying why would you touch something that is so obviously criminal and insane and you know this will this will be the end of your academic career if you go into that field but um I just thought it was just a fascinating anomaly just something that I'd never seen before that so clearly was aligned with everything I knew about you know this is the hayekian sort of story of you know markets and economies as computational devices here it was literally a computational distributed device um so it just it had this I had this sort of intuition that this was something big and something worth of really digging into and um what do you think is I mean what's the meaning of this um what's the reason that it comes from nowhere I mean why is this different um uh what what is the message hidden behind yeah look I I've it's a I've thought about that a lot um what I I think a lot of Technologies can potent do start like this so then I've I've done a lot of work on Innovation Commons I've got a book on this published in 2019 if you want to check that out um but what what the sort of basic Insight here is is that a lot of new technologies that come along and you know if we think of software and soft you know coordination software to create digital scale so this is a new technology um one of the key challenges is it's very very difficult to figure out the economic value of something fundamentally novel because you have to and for Hayek in reasons to to understand the Economic Opportunity of a new technology um it's not enough just to sort of look at it and go well I I foresee a future when lots of people will buy this thing or sell it or whatever um or just you know what you have to do is you have to figure out all of the um we have to assemble a huge amount of information about the costs in building and making it um sources of Supply um potential barriers regulatory barriers and legislative barriers um to to that um potential sources of markets et cetera et cetera et cetera whole lot of information none of that information exists um in one hit usually but the information might exist you know in the world but it's it's different people will have it because they've done experiments they've been playing with it or so yeah we tried that and it does this when you do that it blows up or yeah we tried to find some parts for that and you can get it from there and whatever but that fundamental information problem of how to get all of the information relevant to figure out is this an opportunity is this something that I can make profit on um you know profit in the sense of just creates more value than it uses right not to they use it in an ideologically neutral sense um it's an information problem and it's an information problem that needs to be solved by assembling a whole lot of people that have parts or shards of that information where everyone has bits of information but they don't know the value of what they're holding they might be crucial it might be trivial um you need to get them together in a conditions of extreme uncertainty um to try and figure this out now a firm is good you know a business firm is good when you've kind of got a lot of the information figured out already um you know here's how we're going to do it yeah yeah we just need to assemble the stuff and write the contracts um a Commons is a context when people will come together and just share that information they don't really know what they've got but they want to see what everyone else is holding so as I said right at the start I was studying blockchain and 3D printing but I was also studying the invention of new sports and the invention of new sports you know sort of I think mountain biking in the 1970s or windsurfing in the 1980s or kiteboarding in the early 2000s and so on is usually a bunch of enthusiasts comes together and go did you know if you strap this onto this and hold it like this and go there you can do that and if you do this trick it really hurts but if you do it like this it's a Mexican um so it's mutual sharing of information about stuff with other people but you're not quite sure what you're going to do yet now at some point you'll start a business or at some point people go we should make your business manufacturing these things or selling gear for this or whatever um then you need to figure okay what are the rules how do we govern how do we make this into an actual sport other than just a bunch of people you know moving very very quickly through water um so there's a whole lot of sort of adding layers of technology and adding layers of Institutions and and just you know and eventually it emerges and we have a new thing but the starting point of every new technology that goes into the economic system almost always starts in the comments um just simply because that's the only place where you can get a group of people that come together to pull distributed information under extreme uncertainty to try and discover value so that's the answer to the question why did crypto why why did Bitcoin I mean start in the comments because because all Technologies start there um especially ones that have that are radically new um we just don't tend to sort of you know from a historical perspective we don't have to see that because it doesn't leave a record um it doesn't have a you know the registry of the company or there's no intellectual property in that story there's no firms in that story there's no government grants in that story there's no it's just a bunch of people coming together and sharing information that they're obsessed about um to create things so yeah blockchain more than anything illustrates that process that's interesting and so and based I don't know now that you're telling me this I don't know if you can use previous models of Technology adoption and diffusion I mean but my next question was going to be you know when this is becoming like massive I mean based on previous you know experiences of innovation yeah so that whole common story is very much about the very very early stages so I think a lot of them models of um technology adoption diffusion are actually correct they're just correct for the later stages of it once it gets going and taking off um so I mean this is this is my current sort of this is the the work I'm currently doing um but to sort of write a book or two about this topic but just basically this question of what does it look like with a fundamental Global transition from industrial economies to digital economies what is the nature of that transition look like and what I think the argument is is it's not going to look like the sort of technological trajectories we've seen around adoption diffusion curves if you know phones and you know self-driving cars and washing machines and electricity and so on you have these logistic diffusion curves that just go up and and because what we're dealing with here is institutional Technologies um digital monies digital contracts digital court systems you know this this full sort of stack of digital institutional coordination Technologies and the thing about institutional Technologies unlike Industrial Technologies is Industrial Technologies you can adopt one by one I'll use get a phone and you'll get one and someone asked for and someone else will and so on so um with institutional Technologies there are extremely powerful Network effects but they're also extremely High you have to get to a certain level that they have to sort of work and you know um we all have to agree to adopt the new thing so you've got this huge coordination problem in the in the adoption curve which means that something either has to push them over it um now if you know for instance if you have to have an external forcing function sort of so covert was a famous one that sort of forced everyone to suddenly start using Zoom um just overnight we all had to sort of suddenly adopt this new technology because um so you know we tend to have nation states are very good at forcing that this will be the money we will use this will be the court systems we will use et cetera et cetera um we're now looking at how do we go through a period of Rapid adoption of institutional Technologies where it is not being led by nation states um they're mostly resisting it but instead being led by emergent communities of the use of practice um that are at global scale and so on so I mean that's that's I think where we are at the moment and what this looks like is the the analog of nation states here are high-level communities of use so it might be Gamers or it might be whatever that that is scattered around the world but all have a common use case for this new thing and can adopt it um in that order so I think you know that's that's where we are at the moment in terms of what the dynamic transitions of the world for the next few decades will look like and you know just to recap that I think it doesn't look like industrial Dynamics it's not going to be the 1920s or 50s where we suddenly got aircraft or radio or televisions and computers and so on that sort of trajectory um it's going to be a bit for a start it's Global um this isn't sort of country by country this is this is happening at the global level um secondly it's likely to be um unsmooth it'll be nothing nothing suddenly back and then through and that that that those trigger points could be difficult to predict because they will be conditional upon an accumulation of Kim of of um preparation that suddenly something will trigger the switch and then everyone switches so um this will feel a lot more abrupt and and chaotic than it actually is but I think the Dynamics of institutional technology adoption is different from the Dynamics of industrial technology adoption um in ways that none of us have ever experienced before like you know this this was something that you know Humanity has experienced in the past before um but even then let's go back to the Industrial Revolution or in a periods before that but even then that was a multi-decade process I think it's going to be much faster this time I find very interesting the examples you you are bringing you know um this new sports and this new gamer communities on the internet and also lots of the people I see working on blockchain and entrepreneurs I mean and myself included we we come from places where institutions I mean there was like a void of Institutions I mean I'm from Argentina and I I mean I got into blockchain because of um I could see very clearly what was not working with institutions and I could see that also as a practical problem against Capital controls and I mean all of these and I kind of um I started clearos as some way to answer you know this lack of institutional certainty of you know whatever I don't know what do you think of that yeah like I I this is this is something that is very close to my heart because what you are is an Institutional entrepreneur right and so we have normally entrepreneurship and industrial economy with entrepreneurship in building a new product you know a new widget a new you know type of um thing that you can make and buy and sell whereas what we're seeing in institutional entrepreneurship or innovation was very very rare um it was done through the legislative process it was slow um it's you know institutions hardly changed at all because all of the Dynamics in the economy was in the industrial part of it that were rapidly evolving and changing what we've got now is the opposite of that that we're starting to see this period of Rapid institutional Innovation because we can because the costs of institutional Innovation have fallen so low um if institutions are just made of software um it's easy for me to Fork it download it change it to modify I can I can innovate in institutions far more cheaply um so you know economics demand curve slid downwards When Things fall in price we consume more of them um when institutional Innovation Falls in price we get more institutional Innovation now the the limits of it are adoption that was that I was talking about before that easy to come up with new institutions hard to get people to use them um but I think what we're seeing is this sort of golden age of innovation in institutions in the same way that much of the 20th century was a golden age for innovation in Industrial Technologies um so you know they asked as part of that movement but you know lots of a lot of the things that we're seeing in defy and stable coins and you know um the you know that whole Space huge nfts huge institutional Innovation Innovation um everything we know about Innovation is probably also true here most of it will fail some of it will become huge impossible to know which ones um in advance of just running the program and seeing so there's you know we can't we can't axiomatically figure this out in advance because this one is clearly Superior we just have these things are so complex the only way to figure out what's going to work is just to try it and see um which means that you know that's the move fast try things out iterate et cetera Etc so lots of lots of lessons from Innovations to apply here but um you know it's to me it's very clear what's going on this is innovation entirely new realm of the economy that's that's great I mean I could I mean stay a lot of time speaking with you but I mean just one last question and we will certainly do maybe a another episode uh with all of the questions I didn't get to ask but you know what books movies or documentaries or whatever can you recommend it to people who want to get into this world of evolutionary economics blockchains and everything that you are researching yeah like um so evolutionary economics is a big deep field it actually goes back over 100 years so I said sort of Joseph Sean Porter and there's also Torsten Babylon and so on so there's there's a lot of historical stuff in the in the distance um the modern sort of great institutional economists uh dick Nelson and Sydney winter um hopefully both of them will win the Nobel Prize soon for the work that they've done um they wrote a classic book in 1982 which is 40 years ago um called The Evolution um the remember it evolutionary theory of economic change um that's a good place to start if you want a book but it's um but a lot of the um there's a journal called the Journal of evolutionary economics is a good place to look just to get a sense of the type of work that's going on there um it's it's a it's a very very broad area now that's that's that cuts across things um I would I would suggest um you know I'll plug my own book um integrate The Innovation Commons um that came out a few years ago Marksman University press as a sort of one of the ways of introducing some of the new things in the space but um you know as always with all things Wikipedia is a great place to start this place to start you know what can you recommend to me you know yeah I'm just going to to make one more recommendation there is this very good book by kalota Perez about technological revolutions or financial Capital it's a great humanitarian analysis of economic cycles and how technology change so Jason thank you a lot for for coming do you have any final awards for for the audience no look thank you very much for inviting me on I've thoroughly enjoyed this and my main recommendation is to go back and read the agorak papers Mark Miller's um work from the late 80s it's it's it's um your best chance to see what an actual time traveler looks like and are they right I also support that so thank you very much Jason and this was a new episode of the centralized Justice broadcast I am felicoast and see you in the next episode
2023-02-20