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

0. Jaya Klara Brekke et al. :

"Cryptoeconomics describes an interdisciplinary, emergent and experimental field that draws on ideas and concepts from economics, game theory and related disciplines in the design of peer-to-peer cryptographic systems. Cryptoeconomic systems try to guarantee certain kinds of information security properties using incentives and/or penalties to regulate the distribution of efforts, goods and services in new digital economies. Cryptoeconomics is an embryonic field at present and can be taken to include several areas of focus: information security engineering, mechanism design, token engineering and market design. This portmanteau of cryptography and economics raises questions regarding the epistemic novelty of cryptoeconomics, as distinct from its constituent components."

(https://policyreview.info/glossary/cryptoeconomics)

1. Shermin Voshmgir and Michael Zargham:

"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 governance that reliance on cryptoeconomics currently does or might incur. I review several apparent limitations. These reflect widely recognized attributes of cryptoeconomic systems, and they are sites of active development that may be addressed as practice evolves. But for now, I argue, these limitations suggest that older concerns about the corrosive effects of economics on democratic governance are also relevant to cryptoeconomic domains. At the root of these limitations is the blindness of cryptoeconomics to the identity and integrity of human users—a persistent, but not necessarily permanent condition. In most pre-digital political and economic governance systems, identifying participants is not an existential problem. Difficulties arise in edge-cases. Fraud, which can be minimized with laws that threaten to punish it. Authorities may not have simple processes in place for when citizens’ names or gender identification changes. Refugees crossing borders may have trouble identifying themselves. But many people find that they can take government-based identity infrastructure for granted. Dominant Internet platforms have also come to incorporate users’ politically defined identities into their systems, either directly (such as by requiring government-issued identification) or indirectly (such as through bank accounts or phone numbers).Cryptoeconomics typically seeks to avoid reliance on centralized institutions such as governments. For developers of distributed-ledger systems, representing the personhood of participants is a chronic problem, precisely because of how cryptography obscures its users and how economic incentives reward deception. A common anxiety is the danger of “Sybil” attacks, in which a single user can benefit by masquerading as many users (Conte de Leonet al., 2017). Such attacks can be easy and damaging. Some applications may require users to verify their identities by multiple means, such as by posting a code on social media accounts, producing a video of themselves, and submitting biometric data. In cryptoeconomic contexts, personhood cannot be taken for granted, and establishing it incurs costs. Enduring a complex process of identity verification, for instance, may prevent less-motivated users from completing the on-boarding process, thus reducing adoption.For many blockchain enthusiasts, the lack of reliance on personal identity is a feature not a bug, offering advantages in terms of privacy and permissionless participation. Cryptoeconomics could also produce identification protocols that improve on existing options, such as through “self-sovereign identity”mechanisms based on reputation and mutual attestation of others across a network (Tobin & Reed, 2017). This approach could give users unprecedented control over how they represent themselves and could be less vulnerable to the coercion or collapse of governments. But cryptoeconomics has yet to deliver a widely adopted means of identifying unique human users. Therefore the control of economic units, rather than units based on personhood, remains the basic logic of governance. This presents challenges for governance if personhood should still possess intrinsic importance.

Persistent plutocracy

The prevailing consensus mechanisms, known as “proof of work” and “proof of stake,” 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 similar logic, granting power to whomever holds their tokens. Those with more tokens than others hold more decision-making power than others. Vitalik Buterin (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 conventionally 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 externalities as fair wages and environmental impacts. Yet companies operate within the constraints of state policy, which ultimately govern obligations among state-recognized persons, whether corporate or natural. The earliest companies formed to fulfill the charters of mercantilist monarchs; today, companies must at least adhere to the rules of governments that purport to represent the will of 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, governments can counteract it through progressive taxation, collective bargaining rights,environmental regulations, antitrust enforcement, and more. If distributed ledgers are based on cryptoeconomics “all the way down,” without an underlying political order, such options are not available. But if “a DAO is closer to a country than to a corporation,” participants will expect countermeasures against rule by wealth. For cryptoeconomic systems, as in many economic markets, the primary means of accountability and redress against plutocracy is user exit — leaving one network and moving to a more agreeable one. But exit may not be as 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 cryptoeconomics similarly favors incumbency. Mechanisms like quadratic voting can reduce plutocracy by lessening the influence of large vote-buyers in comparison to smaller ones (Buterin et al., 2018; Wright, 2019–2020). But this comes atthe cost of greater vulnerability to Sybil attacks in the absence of robust means of establishing personhood.

For now, plutocracy may be endemic in cryptoeconomic systems. Ferreira et al. (2019) predict a high likelihood of corporate capture in proof-of-work blockchains 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 plutocracy less attractive (Buterin, 2018; Eyal, 2019). 1Hive counteracts large holders by rewarding non-monetary participation with tokens and making decisions with mechanisms that weigh commitment, not just wealth. But as long as governance is reducible to economics, it will be difficult to prevent the feedback loops between wealth and power from spiraling into plutocratic outcomes.

Suppressing participant interests

Like economics itself, cryptoeconomics is surely normative as well as descrip-tive. Ferraro et al. (2005) find across numerous studies that “self-interested behavior is learned behavior, and people learn it by studying economics and business.” Although this picture of human flourishing finds limited validation in empirical psychology and anthropology,homo economicus has spread across organizational life through managers with economics-informed business education. It shapes the institutions people create, as well as peoplethemselves.The anthropology underlying cryptoeconomic institutional design—“explicit economic incentives for good behavior and economic penalties for ba[d]behavior” (Buterin, 2018)—assumes that users have a common desire to maximize their economic rewards; incentives based on those rewards comprise the structure of organizations and nudge the behavior of participants. Remarkably, cryptoeconomic design has produced multi-billion-dollar financial networks that are resistant to fraud, without government coercion to enforce their 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 field already 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 different meaning if it is a fandom of authors freely sharing fan-fiction, in comparison to Honey-holders in 1Hive who stand to profit from the market value of their shared token. Relying on cryptoeconomic incentives limits governance to a narrow subset of the techniques that other kinds of institutions have used. Cryptoeconomics sees only a certain slice of the people involved. Concepts such as self-sacrifice, duty, and honor are bedrock features of most political and busines sorganizations, but difficult to simulate or approximate with cryptoeconomic incentive 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 economically valuable forms of organizational loyalty often grow out of non-economic forms of relationship. When people complain that others seem to vote against their own economic interests, it should be a reminder that economic interests do 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) found that, while introducing algorithmic processes can increase efficiency, doing so 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-based systems meanwhile have trouble seeing aspects of the world around them not already captured in the algorithms.

Discounting externalities

On May 13, 2021, the billionaire entrepreneur Elon Musk issued a statement that his company Tesla would stop accepting Bitcoin for car purchases due to concerns about the cryptocurrency’s fossil-fuel usage, almost instantly causing a 10 percent dive in Bitcoin’s value (Livni, 2021). In the guise of an erratic celebrity, this was a rare case in which Bitcoin faced at least asemblance of accountability for its country-sized energy consumption and environmental impact. The system is governed by its users—especially the“miners” who carry out its energy-intensive computation—and those users generally 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 lower environmental impact, but the incentives associated with Bitcoin’s dominant market position have prevented mass exodus.

The environmental costs are classic externalities—invisible to the feedback loops that the system understands and that communicate to its users as incentives. Other externalities relevant to distributed ledgers include money laundering, dealings in dangerous drugs and weaponry, tax evasion, and the growth of ransomware attacks on public infrastructure that cryptocurrencies have facilitated. Non-cryptoeconomic systems have some similar properties; shareholders of oil companies also have incentives to pollute, and paper money can support dangerous black markets. But such abuses, at least in principle, are subject to oversight and enforcement by governments tasked with protecting the common good. Political processes enable participants to negotiate compromises among a variety of economic and non-economic interests. If the firm on its own does not see a given externality, the regulatory layer can compel it to do so, such as through disclosure requirements or selective taxation. The externality thus becomes visible to the firm’s incentive structures. For distributed ledgers, similar oversight remains either crude or nonexistent. Cryptoeconomics can accommodate designs that integrate new variables into their incentive structures; Bitcoin could conceivably incorporate a software update with incentives for reducing energy consumption. “Oracle” mechanisms like that of reality.eth, which resulted in Kleros case 532, enable cryptoeconomic systems to take input from arbitrary phenomena that would otherwise be outside the view of their algorithms. “Non-fungible tokens”(NFTs) have made representations of non-quantifiable works of art legible and quantifiable on distributed ledgers. If things must be quantified to be seen, 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 infrastructure that does not produce direct financial returns. Non-market institutions such as governments and (at vastly smaller scales) charities have been necessary for the provision of public goods before cryptoeconomics; increasingly, distributed ledgers are reinventing them through fee-funded treasuries and donor grant pools. In this and other respects, cryptoeconomic designers are beginning to venture into the realm of the political."

(https://osf.io/wzf85/?view_only=a10581ae9a804aa197ac39ebbba05766)

More information

• Crypto Economy ; Cryptoeconomy
• Report: Foundations of Cryptoeconomic Systems

Article

* Article: Brekke, J. K. & Alsindi, W. Z. (2021). Cryptoeconomics. Internet Policy Review, 10(2). doi

URL = https://policyreview.info/glossary/cryptoeconomics

"Cryptoeconomics describes an interdisciplinary, emergent and experimental field that draws on ideas and concepts from economics, game theory and related disciplines in the design of peer-to-peer cryptographic systems. Cryptoeconomic systems try to guarantee certain kinds of information security properties using incentives and/or penalties to regulate the distribution of efforts, goods and services in new digital economies. Cryptoeconomics is an embryonic field at present and can be taken to include several areas of focus: information security engineering, mechanism design, token engineering and market design. This portmanteau of cryptography and economics raises questions regarding the epistemic novelty of cryptoeconomics, as distinct from its constituent components."

(https://policyreview.info/glossary/cryptoeconomics)