Cryptoeconomics
= "a term that has come to describe the mechanics and specifics of token distribution, according to a given sale and ownership structure". [1]
Contextual Quote
"The stateful nature of cryptoeconomic systems has the potential to cede control of data back to the users of these platforms, if privacy by design is considered in the modeling of the cryptoeconomic systems and their applications."
- Shermin Voshmgir and Michael Zargham [2]
Description
Shermin Voshmgir and Michael Zargham:
1.
"Cryptoeconomics is an emerging field of economic coordination games in cryptographically secured peer-to-peer networks. The term cryptoeconomics was casually coined in the Ethereum developer community, and is generally attributed to Vitalik Buterin. The earliest recorded citation is from a talk by Vlad Zamfir [Zamfir 2015], which was later loosely formalized in blog posts and talks by Buterin [Buterin 2017a], [Buterin 2017b]. The term has gained traction in the broader developer community [Tomaino 2017a] and in the academic community [Catalini and Gans 2016], but it still remains under-defined, possibly because it is often used in so many different contexts. Using the same term in different contexts leads to communication breakdowns and challenges when trying to come up with a rigorous definition of that term."
(https://epub.wu.ac.at/7782/1/Foundations%20of%20Cryptoeconomic%20Systems.pdf)
2.
"Cryptoeconomic systems are complex socioeconomic networks defined by
(i) individual autonomous actors,
(ii) economic policies embedded in software (the protocol or smart contract code), and
(iii) emergent properties arising from the interactions of those actors with the whole network, according to the rules defined by that software.
A comprehensive definition of cryptoeconomics therefore includes three levels of analysis:
(i) micro-foundational, relating to agent level behaviors
(ii) meso-institutional, relating to policy setting and governance and
(iii) macroobserverable, relating to the measurement and analysis the system level metrics."
Typology
Shermin Voshmgir and Michael Zargham:
"Cryptoeconomics relates three interactions layers or levels of analysis that define characteristics at the micro-foundational, meso-institutional, and macroobserverable domains of scope.
- a Macro-observables are system global properties that inform decision-making
at the meso-institutional level and provide stakeholder feedback, performance indicators and measures that can impact micro-foundational properties.
- b Meso-institutional characteristics encompass decision-making and goal determination, based upon and requiring micro-foundations. Mechanism design as
used in Economics informs institutions, organisations and teams.
- c Micro-foundational characteristics are assumption specifications with a natural expression within mechanism design as used within Computer Science.
Informal Governance is a form of decentralized governance whereby changes to the protocol are made locally by individual participants operating nodes in the peer-to-peer network and changes only take effect if the majority of participants adopt the change."
((https://epub.wu.ac.at/7782/1/Foundations%20of%20Cryptoeconomic%20Systems.pdf)
Examples
"A cryptoeconomic system such as the Bitcoin network can be described as a special class of complex socioeconomic system that is dynamic, adaptive, and multi-scale. Cryptoeconomic networks are dynamic due to the flow of information and assets through the network. Cryptoeconomic networks are adaptive because their behaviour adjusts in response to their environment, either directly in the case of the Bitcoin difficulty controller or more broadly through decisions on the part of node operators. Cryptoeconomic networks are multi-scale because they are specified by local protocols but are defined by their macro-scale properties, as is the case with the local ”no double spend” rule guaranteeing a globally conserved token supply [Zargham, Zhang and Preciado 2018]. Their design requires a strong interdisciplinary approach to develop resilient protocols that account for the spatial and temporal dynamics of those networks [Liaskos, Wang and Alimohammadi 2019]."
(https://epub.wu.ac.at/7782/1/Foundations%20of%20Cryptoeconomic%20Systems.pdf)
Discussion
A UNIFYING PERSPECTIVE ON CRYPTOECONOMICS
Shermin Voshmgir and Michael Zargham:
"Cryptoeconomic systems are complex socioeconomic networks defined by
(i) individual autonomous actors,
(ii) economic policies embedded in software (the protocol or smart contract code), and
(iii) emergent properties arising from the interactions of those actors with the whole network, according to the rules defined by that software.
A comprehensive definition of cryptoeconomics therefore includes three levels of analysis:
(i) micro-foundational, relating to agent level behaviors
(ii) meso-institutional, relating to policy setting and governance and
(iii) macroobserverable, relating to the measurement and analysis the system level metrics.
Critically, the dynamics at each
level of analysis are interdependent in a manner which cannot be simply reduced into a single layer–governance
is precisely managing the relationship between the micro and macro scales.
Micro-foundational characteristics of cryptoeconomic systems are commonly expressed in terms of algorithmic game theory in the computer science literature [Nisan et al. 2007] and mechanism design in the economics
literature [Hurwicz and Reiter 2006]. Mechanism design is sometimes referred to as reverse game theory as it pertains to the construction of games to produce specific behaviors from agents. Nakamoto Consensus, for example,
is a cryptoeconomic mechanism based on proof-of-work that is designed to provide convergence to a dynamic
equilibrium–a synchronous shared global state, which furthermore remains resistant to a range of attacks constituting of self-interested misinformation despite being a permissionless network. An attack would be any violation
of the state transition rules encoded in the protocol, such as a “double spend’. Nakamoto consensus uses a combination of cryptographic tools with economic incentives that make economic cost of wrongdoing disproportionate
to the benefit of doing so [Nakamoto 2008], [Antonopoulos 2014]. Proof-of-stake mechanisms provide similar
game theoretic arguments for network security. Interestingly, proof-of-authority networks [De Angelis et al. 2018]
offer a more traditional approach where the validator role is permissioned and stems from social and institutional
reputational processes which exist outside the computational environment. Most current definitions of cryptoeconomics focus on this level of analysis and modeling [Buterin 2017a], [Buterin 2017b] [Tomaino 2017a]. However,
the level of security very much depends on how people react to economic incentives, which in turn has been a field
of study in economics [Voshmgir 2020]; the security of the network is an emergent macro level property.
Macro-observables are system-wide metrics or properties which may inform decision-making of stakeholders
within the system. Macro-observables often include performance indicators that impact governance decisions
at the meso-institutional level as well as measures that can impact perception and thus behavior at the microfoundational level. In addition to security, market capitalization, price [Shorish 2019], [Cong, Li and Wang 2019]
and price stability are the most commonly studied macro-observables. Other important macro-observables include
wealth distributions, governance participation, monthly active users, and any other measure or estimate which
serves as a proxy for system level goal that matters to a cryptoeconomic network’s human stakeholders. Critically,
macro-observables are not directly controllable; efforts to impact these metrics are determined at the meso scale
and the consequences of those interventions are borne out at the micro scale.
Meso-institutional characteristics encompass decision-making and goal determination, based upon macroobservables and requiring micro-foundations. This level builds on political science, law, governance and economics to design the steering processes of communities, by some referred to as institutional cryptoeconomics [Berg, Davidson and Potts 2019]. Ethical design and informed governance of cryptoeconomic systems resides in the meso-institutional level and requires an understanding of both the micro-foundations and macro-observables, as well as the relations between them. This manuscript, as a whole, addresses the meso-instutional perspective as a keystone in the coherent synthesis of macro and micro perspectives on cryptoeconomics through the observation that automation in socioeconomic systems is tantamount to algorithmic policy making."
The Limitations of Cryptoeconomic Governance Mechanisms
Nathan Schneider:
"The purpose of this section is to identify the limitations on governancethat reliance on cryptoeconomics currently does or might incur. I reviewseveral apparent limitations. These reflect widely recognized attributes ofcryptoeconomic systems, and they are sites of active development that may beaddressed as practice evolves. But for now, I argue, these limitations suggestthat older concerns about the corrosive effects of economics on democraticgovernance are also relevant to cryptoeconomic domains.At the root of these limitations is the blindness of cryptoeconomics to the12 identity and integrity of human users—a persistent, but not necessarilypermanent condition. In most pre-digital political and economic governancesystems, identifying participants is not an existential problem. Difficultiesarise in edge-cases. Fraud, which can be minimized with laws that threatento punish it. Authorities may not have simple processes in place for whencitizens’ names or gender identification changes. Refugees crossing bordersmay have trouble identifying themselves. But many people find that theycan take government-based identity infrastructure for granted. DominantInternet platforms have also come to incorporate users’ politically definedidentities into their systems, either directly (such as by requiring government-issued identification) or indirectly (such as through bank accounts or phonenumbers).Cryptoeconomics typically seeks to avoid reliance on centralized institutionssuch as governments. For developers of distributed-ledger systems, represent-ing the personhood of participants is a chronic problem, precisely because ofhow cryptography obscures its users and how economic incentives rewarddeception. A common anxiety is the danger of “Sybil” attacks, in whicha single user can benefit by masquerading as many users (Conte de Leonet al., 2017). Such attacks can be easy and damaging. Some applicationsmay require users to verify their identities by multiple means, such as byposting a code on social media accounts, producing a video of themselves, andsubmitting biometric data. In cryptoeconomic contexts, personhood cannotbe taken for granted, and establishing it incurs costs. Enduring a complexprocess of identity verification, for instance, may prevent less-motivated usersfrom completing the on-boarding process, thus reducing adoption.For many blockchain enthusiasts, the lack of reliance on personal identity is afeature not a bug, offering advantages in terms of privacy and permissionlessparticipation. Cryptoeconomics could also produce identification protocolsthat improve on existing options, such as through “self-sovereign identity”mechanisms based on reputation and mutual attestation of others across anetwork (Tobin & Reed, 2017). This approach could give users unprecedentedcontrol over how they represent themselves and could be less vulnerable to thecoercion or collapse of governments. But cryptoeconomics has yet to delivera widely adopted means of identifying unique human users. Therefore thecontrol of economic units, rather than units based on personhood, remainsthe basic logic of governance. This presents challenges for governance ifpersonhood should still possess intrinsic importance.13 Persistent plutocracyThe prevailing consensus mechanisms, known as “proof of work” and “proof ofstake,” grant governance rights roughly in proportion to a given node’s buy-inon the network—through computing power or token holdings, respectively.Applications and organizations built on such networks tend to follow a similarlogic, granting power to whomever holds their tokens. Those with moretokens than others hold more decision-making power than others. VitalikButerin (2018) therefore comes by his anxieties about plutocracy honestly;rule according to wealth has so far been the norm in cryptoeconomic designs.Governance by economics is nothing new. Joint-stock companies conven-tionally operate on plutocratic governance—more shares equals more votes.This arrangement is economically efficient for aligning shareholder interests(Davidson and Potts, this issue), even while it may sideline such externalitiesas fair wages and environmental impacts. Yet companies operate within theconstraints of state policy, which ultimately govern obligations among state-recognized persons, whether corporate or natural. The earliest companiesformed to fulfill the charters of mercantilist monarchs; today, companies mustat least adhere to the rules of governments that purport to represent the willof society as a whole, not just the company’s participants. Governments im-pose rules about transparency, conduct, accounting, equity trading, and more.So while plutocracy is prevalent in the joint-stock universe, governmentscan counteract it through progressive taxation, collective bargaining rights,environmental regulations, antitrust enforcement, and more. If distributedledgers are based on cryptoeconomics “all the way down,” without an under-lying political order, such options are not available. But if “a DAO is closerto a country than to a corporation,” participants will expect countermeasuresagainst rule by wealth.For cryptoeconomic systems, as in many economic markets, the primarymeans of accountability and redress against plutocracy is user exit—leavingone network and moving to a more agreeable one. But exit may not beas easy as it appears, whether it be from a social-media network (Matias,2018) or a protocol (Galloway, 2006). The persistent dominance of early-to-market blockchains like Bitcoin and Ethereum suggests that cryptoeconomicssimilarly favors incumbency. Mechanisms like quadratic voting can reduceplutocracy by lessening the influence of large vote-buyers in comparison tosmaller ones (Buterin et al., 2018; Wright, 2019–2020). But this comes atthe cost of greater vulnerability to Sybil attacks in the absence of robustmeans of establishing personhood.14 For now, plutocracy may be endemic in cryptoeconomic systems. Ferreiraet al. (2019) predict a high likelihood of corporate capture in proof-of-workblockchains such as Bitcoin. Many hope that the influence of venture-capital firms in token markets might be warded off with efficient vote-selling(Automata Finance, 2021) or other incentive designs that make plutocracyless attractive (Buterin, 2018; Eyal, 2019). 1Hive counteracts large holdersby rewarding non-monetary participation with tokens and making decisionswith mechanisms that weigh commitment, not just wealth. But as longas governance is reducible to economics, it will be difficult to prevent thefeedback loops between wealth and power from spiraling into plutocraticoutcomes.Suppressing participant interestsLike economics itself, cryptoeconomics is surely normative as well as descrip-tive. Ferraro et al. (2005) find across numerous studies that “self-interestedbehavior is learned behavior, and people learn it by studying economicsand business.” Although this picture of human flourishing finds limitedvalidation in empirical psychology and anthropology,homo economicushasspread across organizational life through managers with economics-informedbusiness education. It shapes the institutions people create, as well as peoplethemselves.The anthropology underlying cryptoeconomic institutional design—“expliciteconomic incentives for good behavior and economic penalties for ba[d]behavior” (Buterin, 2018)—assumes that users have a common desire tomaximize their economic rewards; incentives based on those rewards comprisethe structure of organizations and nudge the behavior of participants. Re-markably, cryptoeconomic design has produced multi-billion-dollar financialnetworks that are resistant to fraud, without government coercion to enforcetheir claims. Yet perhaps the anthropology embedded in these systems—thathomo crpytoeconomicusof incentive nudges—helps explain why distributed-ledger adoption has been primarily among finance-related applications, a fieldalready premised on self-interested value-maximizing. Outside of finance,people might expect systems that can see different sides of their natures.The subjectivity of a cryptoeconomic juror on Kleros seeking to earn afee is surely different from that of jurors deliberating in a legal courtroom,repeatedly reminded of their civic duty. “Community” takes on a differentmeaning if it is a fandom of authors freely sharing fan-fiction, in comparisonto Honey-holders in 1Hive who stand to profit from the market value of their15 shared token.Relying on cryptoeconomic incentives limits governance to a narrow subset ofthe techniques that other kinds of institutions have used. Cryptoeconomicssees only a certain slice of the people involved. Concepts such as self-sacrifice, duty, and honor are bedrock features of most political and businessorganizations, but difficult to simulate or approximate with cryptoeconomicincentive design. Labor unions can produce economic benefit for members,but achieving and maintaining those benefits has required cultivating an“expanded community of fate” that is anything but self-interested (Levi, 2020).As Albert O. Hirschman (1970) famously showed, the most economicallyvaluable forms of organizational loyalty often grow out of non-economic formsof relationship. When people complain that others seem to vote againsttheir own economic interests, it should be a reminder that economic interestsdo not encapsulate the totality of human needs and wants (Haidt, 2012).Governance regimes should reflect that multiplicity.In a survey of diverse governance domains, Gritsenko & Wood (2020) foundthat, while introducing algorithmic processes can increase efficiency, doingso also results in “decreasing the space for governing actors’ discretion.”Algorithms can also increase the space of their initial designers’ power,compared to the power of future users (Galloway, 2006). Incentive-basedsystems meanwhile have trouble seeing aspects of the world around themnot already captured in the algorithms.Discounting externalitiesOn May 13, 2021, the billionaire entrepreneur Elon Musk issued a statementthat his company Tesla would stop accepting Bitcoin for car purchases dueto concerns about the cryptocurrency’s fossil-fuel usage, almost instantlycausing a 10 percent dive in Bitcoin’s value (Livni, 2021). In the guise ofan erratic celebrity, this was a rare case in which Bitcoin faced at least asemblance of accountability for its country-sized energy consumption andenvironmental impact. The system is governed by its users—especially the“miners” who carry out its energy-intensive computation—and those usersgenerally stand to benefit from ignoring their collective carbon footprint.A busier network roughly correlates to higher energy consumption anda higher trading price. Competing cryptocurrencies have promised lowerenvironmental impact, but the incentives associated with Bitcoin’s dominantmarket position have prevented mass exodus.16 The environmental costs are classic externalities—invisible to the feedbackloops that the system understands and that communicate to its users asincentives. Other externalities relevant to distributed ledgers include moneylaundering, dealings in dangerous drugs and weaponry, tax evasion, and thegrowth of ransomware attacks on public infrastructure that cryptocurrencieshave facilitated.Non-cryptoeconomic systems have some similar properties; shareholders ofoil companies also have incentives to pollute, and paper money can supportdangerous black markets. But such abuses, at least in principle, are subjectto oversight and enforcement by governments tasked with protecting thecommon good. Political processes enable participants to negotiate compro-mises among a variety of economic and non-economic interests. If the firmon its own does not see a given externality, the regulatory layer can compelit to do so, such as through disclosure requirements or selective taxation.The externality thus becomes visible to the firm’s incentive structures. Fordistributed ledgers, similar oversight remains either crude or nonexistent.Cryptoeconomics can accommodate designs that integrate new variables intotheir incentive structures; Bitcoin could conceivably incorporate a softwareupdate with incentives for reducing energy consumption. “Oracle” mech-anisms like that of reality.eth, which resulted in Kleros case 532, enablecryptoeconomic systems to take input from arbitrary phenomena that wouldotherwise be outside the view of their algorithms. “Non-fungible tokens”(NFTs) have made representations of non-quantifiable works of art legibleand quantifiable on distributed ledgers. If things must be quantified to beseen, however, what meaning might be lost in the process of quantification?The challenge of funding “public goods” is another example of an externality—and one that threatens the sustainability of crypteconomic systems (Buterinet al., 2018). As has been the case for commons-based software in general (Arpet al., 2018), market mechanisms struggle to support critical infrastructurethat does not produce direct financial returns. Non-market institutions suchas governments and (at vastly smaller scales) charities have been necessary forthe provision of public goods before cryptoeconomics; increasingly, distributedledgers are reinventing them through fee-funded treasuries and donor grantpools. In this and other respects, cryptoeconomic designers are beginning toventure into the realm of the political."
(https://osf.io/wzf85/?view_only=a10581ae9a804aa197ac39ebbba05766)