IEEE Blockchain Podcast Series: Episode 4
A Conversation with Jason Potts
Co-Director, RMIT Blockchain Innovation Hub, RMIT University
Listen to Episode 4 (MP3, 39 MB)
Part of the IEEE Blockchain Podcast Series
Brian Walker: Welcome to the IEEE Blockchain Podcast Series, an IEEE Digital Studio production. This new blockchain series entitled Research Notes in Blockchain is hosted by Quinn DuPont, Assistant Professor at the University College Dublin School of Business, and the author of “Cryptocurrencies and Blockchains.” Professor DuPont interviews Jason Potts, Professor of Economics and Codirector of Blockchain at RMIT University Melbourne. Professor Potts provides economist views on the benefits and challenges of blockchain as it relates to institutional cryptoeconomics and provides his insights on trust and governance in the design and utilization of cryptocurrencies.
Quinn DuPont: So, your background is in economics, which let’s just start with-- in a rather surprising way, it seems like economists haven’t really embraced the study of cryptocurrencies and blockchains as one might have imagined they would have. So, if you had to make a case for more involvement by the economics profession more generally, where would you start? More generally, what are the tools you think an economist brings to the study of cryptocurrencies and blockchains?
Jason Potts: Yeah. It’s an interesting question. Economists have been late to analyze the nature of cryptocurrencies and blockchain and I think a large part of that is that they misunderstood what it is and what they looked at it and saw was “Oh, that’s a money. We know about money. We’ve got theories with money. This looks like a not very good money,” and just walked away from it, more or less at that point and what they failed to see-- and I think they failed to see it in a sense because they were just simply too close to it. Blockchain, cryptocurrencies are basically made of economic incentives. That’s a core part of the technology, but what they failed to see was what they were looking at was essentially an artificial economic system or an artificial economic mechanism that was providing not just money, but rules, rules of the game, governance, organizational structure, payments, infrastructure. So, what you’ve actually got is to explain why cryptocurrencies and blockchain technology is significant to economists, you have to actually start with the idea that what they’re looking at here is an artificially designed economic system and once they can make that leap, a lot of things fall into place, but I think the idea that it was “Cryptocurrency, which is just a money, but not a very good one because we’ve already got money,” has misled an entire generation of economists.
Quinn DuPont: Interesting. Are there any particular areas of focus that economists have dealt with traditionally that you think are particularly pertinent to the study?
Jason Potts: Yeah. There’s quite a few areas that economists are focused on. Obviously, indicated the first step is the nature of money and what that has unpacked-- and this is a traditional area of monetary economics and macroeconomics is the idea of quality of money, that money can have different qualities where we’re normally used to thinking of money as being something that is basically supplied as a monopoly good and not competitively supplied with enabling it to have different features. So, a programmable money can obviously have a lot more dimensions and features that a government supplied money that is just “This is what it does.” I think the broader and more interesting aspects of this in relation to contracts, contracting, and the automation of trust and a lot of what blockchain technologies, smart contracts in particular facilitate is the ability for someone to use promise, to make a promise, and to have that promise of self-enforcing and what you end up with then is that instead of-- I think the main sort of impact on the economy or on economic structure is not just a new payments technology or a new monetary technology, but a new governance technology or a new way of organizing economic systems. So, what we have then is just a basic prediction here that hierarchical organizations, firms and corporations and so on are just simply less efficient compared to the ability to now use smart contracting technologies to organize economic activity. So, markets and contracting will work comparatively better because it’s just lower cost, easier to enforce, and hierarchical organizations, firms and governments in particular, will be comparatively less efficient. That’s a shift in the organizational structure of an economy that this technology makes possible and that’s something that economists are still-- they’re very much in the center of economics and the idea of what does this do to the organizational structure of an economy is the key question here.
Quinn DuPont: This you’ve called institutional cryptoeconomics, which we’ll get into, but before we do that, maybe we can talk a little bit about just this sort of concept or emerging field of cryptoeconomics and to me, it seems like there’s multiple and perhaps incommensurable definitions. For instance, Vitalik Buterin, famous co-creator of Ethereum, makes broad use of game theory, especially Nash equilibrium. So, there’s these multiple definitions, but what would you say would be a good kind of way of understanding cryptoeconomics and specifically, what does this field of cryptoeconomics offer blockchain engineers and designers?
Jason Potts: So, cryptoeconomics, in the sense that Vitalik Buterin-- I think he actually coined the phrase in that space and he’s not an economist by training, but he’s one of the most natural economists I think I’ve ever come across. But cryptoeconomics is essentially the idea of using mechanism design, which is just reverse game theory as a way to design incentive systems or to design incentive mechanisms to enable blockchains to work, which will enable cryptocurrencies to work. It’s using the tools of game theory and mechanism design to create-- it’s an engineering approach to create high-powered incentives for whatever it is you want your token to do. In that sense, cryptoeconomics is a branch of economics in the same way that engineering-- we use engineering to build and design physical systems that we want them to have certain properties, we use cryptoeconomics for the same thing. So, game theory applied to token design is the classic understanding of what cryptoeconomics is. What’s buried in there is that there’s also-- it’s part just engineering design of incentives, but those are incentives for humans to follow. So, there’s also a little bit of behavioral economics mixed up in that as well, where you’re designing systems where the main incentive is usually a price mechanism or some sort of monetary reward to incentivize behavior that you want as an outcome. That’s the classic definition of what cryptoeconomics is, as a design science.
Quinn DuPont: So, let’s drill in a little bit further into what you call-- you and your colleagues at RMIT call institutional cryptoeconomics. If I can, it seems to me that you argue they address sort of three key issues. The first is opportunism or maybe what might be called the desire to cheat, then there’s bounded rationality, which is the fact that I don’t know everything, and then asset specificity, which is to say that some assets cannot be adapted or transformed easily and so, some of this work comes out of Coast and then Williamson and what the traditional answer is results in hierarchal firms to solve these issues, but you, if I’m correct, argue that blockchains can do much the same. Can you explain a little bit why and how that might happen?
Jason Potts: Yeah. So, the basic argument we make here-- this builds upon this idea of cryptoeconomic systems as using mechanism design to design high-powered incentives-- there’s lots of design of high-powered incentives in an economic system and these include things like firms and markets as well as mechanisms for coordinating economic activity. The basic answer to the question what is a market? What is a firm? -- Underneath these things, you have contracts and contracts need to be written, which is a problem of specifying all of the conditions under which they will hold. The limits to that are what Herb Simon called bounded rationality. I might not be able to imagine or understand all of the possible worlds in which this contract needs to be written, then the situations where the world will subsequently change as it inevitably will and contracts will need to be renegotiated or rewritten or interpreted, and so on. So, what you have then is an economic system in the sort of classical industrial sense of it, is embedded in complete contracts and organizational structures that are designed to deal with this. So, that’s what I’ve affirmed with managers and people sort of using voice and instructions to organize resources are doing. So, you have a lot of mechanisms in an economic system to coordinate just in a fairly complex cooperation and interactions, contracts, firms, and the like. There are a number of problems in that space. So, one of the key ones is simply opportunism, when we’re dealing with the fact that once we’ve established a set of assets and contracts and so on, it’s easy for me to renege if I know it’s costly for you to renegotiate. So, there’s we can exploit these opportunities. The core idea of institutional cryptoeconomics is just to represent the idea that in some cases, being able to lock these contracts in, in code and have them self-enforced, like not actually have it up to human discretion, produces huge efficiencies by just simply taking off the table the ability of counterparties to cheat or counterparties to exploit the fact of contractual ambiguities or the need for us to reach agreement about a thing. So, that notion of digitally enforced contracting, smart contracts, significantly reduces the opportunities for exploitation or what Oliver Williamson-- the Nobel Prize-winning economist Oliver Williamson called opportunism in organizations and market situations and this is important because a huge amount of economic activity from just managerial monitoring, from regulatory oversight, from just the existence of all sorts of administrative overhead costs, exists for no other reason than just to keep everyone honest, to check everyone else’s work, to ensure the agreements are actually followed through on and that’s a huge overhead cost in an economy that can be significantly reduced through automation that comes through smart contracting. So, institutional cryptoeconomics is just looking at the idea that an entire economic system of firms and markets and contracts and legal agreements and people working in organizations and making promises to each other can run significantly more efficiently whenever it is possible for these agreements to be digitally enforced through blockchains. We actually see-- a core argument is that that’s the huge advantage that the blockchain brings is organization or institutional efficiencies are enabling contracts and promises to work better and that’s a different argument to saying, “And you also have cryptocurrencies, which is better money,” and program your money. You get that as well, but institutional cryptoeconomics is the argument of taking institutional economics and what it says about the types of organizational efficiencies that you can design into an economy and recognizing that digital automation of these things through blockchains, through enabling to work in a decentralized way produces significant-- on some margins, in some places, but in important places, gains in efficiency and productivity and contracting. Now, what that then means is that a global decentralized market economy should just work a whole lot better, and we think that’s the reason to be excited about this technology for the coming decades is this productivity improvement in how contracting works can drive huge efficiencies throughout all parts of the economy that’s institutional cryptoeconomics is the study of that, institutional economics applied to digital contracting.
Quinn DuPont: Okay. So, let’s dig in a little bit more into smart contracts. You mentioned incomplete contracts. Of course, the opposite would be complete contracts. What’s an incomplete contract and how does it relate to a smart contract? Maybe also while you’re at it, if you could say something about how trust is modulated within the sort of model of transaction cost analysis.
Jason Potts: So, complete contracting is what it says on the box. It means when I can specify in my contract all of the contingencies to a contract and write those down and you agree to them and this way, we’ve got a contract that will deliver what we both agreed to in our bargaining situation, but also deal with all of the various contingencies. Now, the key point is that that’s costly to do. If we can write a simple contract saying you’ll deliver me one cow on Wednesday or whatever the contract is, that’s fine. I didn’t specify what size of cow. I didn’t specify what time on Wednesday. I didn’t specify what happens if something happens on Tuesday that makes that difficult. We can write a more complete contract by putting more time and effort into doing so. The implication is that at some point, it’s just not worth doing that. At some point, we’ll just go “Look, we’ll figure it out. We’ll use trust to deal with any contingencies or specifications that are required in the future.” Lots of contracting works like that and the most obvious one is employment contracting. Your job contract doesn’t specify in great detail what you’re going to be doing next Wednesday. It just roughly says who you’re working for, who your current boss is, the amount you’ll be paid and everything else will be worked out on the fly. That’s a situation-- employment contracting is actually one where smart contracting wouldn’t work very effectively. Smart contracting works well when we can specify in reasonably complete detail all of the terms of the contracting. So, smart contracts work fantastic for finance, where we’ll have all of the terms of the data instrument or whatever it is that the conditions. So, different areas of the economy are more amenable to fully detailed contracting and wherever that happens, we can push smart contracting into that world, and we can expect it to just lower the cost of all of the other mechanisms of dealing with trust, such as regulatory enforcement or managerial oversight and other such things. So, wherever trust is cheap, we’ll tend to not use smart contracting. So, trust is cheap when we know each other very well, when we’re dealing with a very local situation. Trust is expensive when I’m dealing with strangers, when I’m dealing with people that I’ve never met before. They might be in a foreign land. It makes it difficult for me to enforce a contract. There’s different circumstances under which trust is expensive and contracting is expensive and that sort of equilibrium of what things get written in complete contracts and what stuff do we rely on, mechanisms of trust, including management and monitoring and other ways of enforcing the spirit of a contract. So, smart contracting technology shifts where that line is by enabling us to move more and more into the space of complete contracting. That said, the fundamental limitation of the realms of smart contracting, of where we can push it is we have to be able to specify in reasonably complete detail or contingencies of the world or have ways of writing things that will happen in the real world into statements in a contract in code that can be recognized, it’s the limits of what we can do with smart contract and blockchain. But I think what’s also interesting here is that’s an open technological possibility. So, the whole space of oracles, for instance, or other ways of other technologies that communicate facts about the real world, whether these are price oracles or event oracles or whatever it is to feed into smart contracting increases the space of what we can potentially write and the types of economic activity we can coordinate using smart contracting and its full digital infrastructure. So, I think what we’re seeing at the moment is a world where that space is still-- most contracts in the world have a lot of contingencies and openness and incompleteness built into them for efficiency reasons, but as the digital economic infrastructure of smart contracting and oracles and all of the other components of that-- and lots of things in DFI are feeding into this now-- is going to be just rolling out the space of new economic institutions that are increasingly natively digital and as economic institutions of coordination, contracting enforcement, monitoring, and so on become increasingly natively digital, we can get the efficiencies that come from just very, very low cost execution and delivery of contracting. This is, again, this is the-- from the industrial revolution onwards to relatively recently, so much of the gains of productivity and wealth in an economy came from improving physical technologies, ability to do work better, faster, cheaper with more power and more strength and so on. What we’re entering into now is a world where technologies are pushing into contracting, this ability to coordinate amongst strangers of ever greater scale and complexity and this is the-- right at the center of that is this question of complete and incomplete contracting.
Quinn DuPont: So, it’s interesting that you say trust is a cost, which, of course, is probably only something an economist would say. But you also point out in your most recent work, your book with your colleagues at RMIT, you talk about governance as a cost as well, which is an interesting kind of counterintuitive way of looking at this and maybe you can just say a little bit more about what governance means in the context of blockchain and specifically why engineers and developers should really be aware of this.
Jason Potts: Let me start with why trust is a cost. So, trust is often, from a human psychological perspective, seen to be a good thing that good people have, that a trusting society is a good society. The reason for that is in a world without trust, it’s just very expensive for me to interact with you because you can make promises to me, but they’re meaningless. I have to spend a lot of time and effort monitoring what you’re doing and so on. So, trust is-- when counterparties have trust with each other, they can coordinate very cheaply. They don’t have to spend a lot of effort checking each other’s work and monitoring what they’re doing. They can just let them get on with it. So, we can think of trust as a kind of capital in that sense, that the more resources we put into the quality of trust, the lower the cost of coordination that we can do in an economy. We did some recent work on this where we tried to estimate how much do we actually spend on trust in the economy and the number we came up with was very back of the envelope, but about a third of the economy is just people checking other people’s work. The entire accounting profession is nothing but people checking other people’s work, large amounts of management, the entire regulatory apparatus of government is just people checking other people’s work. Trust is a cost, but that means improvements in technologies of trust reduce those costs and therefore bring benefits for the ability of people to cooperate and coordinate increasingly at scale. So, that’s the sense in which trust is a cost, yes, therefore reductions in the cost of trust are good because they enable us to cooperate and coordinate better. Governance is the same thing. Governance is an aspect of this, where the reason we have governance is when we just need to update agreements that we’ve made or when we need to monitor what someone else is doing, agency costs-- if I supply capital to your organization and you’re now an entrepreneur or a manager using my capital, I need to monitor what you’re doing with that, just to ensure that I’m not being exploited and the terms of the contract, I’ll give you this capital in return for such and such, whatever, are being met. Governance is an aspect of me designing rules to lower the cost of that or to minimize the ability of you to exploit me. Again, that’s mechanism design, that’s in the zone we of what we talked about earlier with cryptoeconomics. But governance just arises when there’s multiple people involved that need to arrive at cooperative agreements with each other, contracting, but it’s costly to monitor and enforce those and also costly to change those as things go on. So, we need governance mechanisms whenever the world is open and complex and contracts are complete and we’re going to need to change our agreements going forward and the more complex the organization you’re building or the more complex the contractual apparatus you’re building, the more you need governance mechanisms to protect everyone in that space. So, governance is just-- it’s also a design science in the sense that you’re trying to design a series of mechanisms that will incentivize counterparties or agents or just other parties to agreements to behave in ways that other parties-- if I’m providing capital, for instance, it’s the classic example of the need for governance, but just to ensure that everyone is behaving in ways that they agreed to. So, governance is sort of like rules of the game in the game theoretic sense. Governance is also a choice. You can have more of it or less of it. The more you put in, the more costly it is because you’re requiring more-- you’re putting more conditions on other parties, you’re requiring more effort involved in monitoring, a classic exercise of governance is voting, for instance. Voting is costly in time and effort and gathering information and forcing votes and ensuring it all takes place. The least costly form of governance is no governance at all, where you just write the rules and let it run. In the sense, you can think of-- in cryptocurrency space, bitcoin has minimalist governance. The rules are just there. It’s very, very hard to change them. There’s a core group that is responsible for that, but that’s minimal governance. That also means those rules can’t be-- you better be sure those are the good rules that you want going forward under all circumstances. Different token ecosystems have different levels of governance. The more complex those rules are, the more variable they are, the more costly that is, but what you get in return is the ability of those rules to adapt to new circumstances or to be able to live in a more complex world. In that sense, it’s just a tradeoff. Governance isn’t an unmitigated good, where more of it is always better. More of it enables greater flexibility to a world of change or an ability to renegotiate contracts, but governance itself is a costly mechanism. The more you put in, the more sunk costs or involved in monitoring who is party to governance, how is this working, gathering information in changing and updating rules and so on. So, at some point, you can sort of conceptualize this idea of there’s an optimal level of governance that isn’t-- it’s somewhere between zero and one, as it were, just in a same way that that is also true of trust. Zero trust is horrible because all you do is spend your time monitoring the counterparty. Complete trust is lovely, but it’s also incredibly expensive to build because it only works in a very narrow circumstance of people who know everything about all of the counterparties and have perfect enforcement over them. So, again, what we’ve got is a convex solution space. Governance and trust are required or invite institutional tradeoffs between the problems of monitoring and the costs of that versus the benefits of being able to renegotiate contracts and live in an open world where you don’t have to specify everything in advance.
Brian Walker: Thank you for listening to our interview with Professor Jason Potts. To learn more about the IEEE Blockchain Initiative, please visit our web portal at blockchain.ieee.org.