Based on my research over the past couple of years, I’ve put together a list of ten theses on decentralized network governance, including base layer public blockchain networks and applications (smart contracts) running on top of them. The ten ideas are listed from the more general and theoretical (descriptive) to the more specific and practical (prescriptive). The first five are revised summaries of my previous writing; the latter five are derived from more recent observations.
I define governance as the process of applying any design feature or control mechanism that maintains and steers a system.
1. Blockchain-related technological and institutional innovation is part of an ongoing maturation phase of the Information Technology (IT) Revolution, which includes the emergence of IT-native forms of socio-economic organization that are digital, global, and increasingly decentralized and automated.
It is in the latter phases of a technological revolution that its key technologies begin transforming the institutional structure of society. Blockchain and related innovations are part of a more general trend towards digitization, computerization, and automation — a world in which a growing number of systemically important processes rely on formal rules of protocol, geared towards more efficient coordination in the context of growing complexity. Although disruptive on the surface, this trend is part of the evolution of an earlier form of organizing that sociologists refer to as bureaucratic. But instead of human administrators, the mundane rule-following in administering information and facilitating transactions connected to that information is increasingly done by distributed networks of machines, some of which are global in their reach.
2. Decentralized networks are fields — social arenas of symbolic and material production in which interested actors compete and cooperate over network-specific resources as they provision and consume the products and services available in the network.
An important precondition for constructing a field — a game worth playing — is socially distributed information about resources at stake, and at least some shared understanding of why these resources are valuable. The structure of a particular field is determined by the distribution of these resources, and by extension, the relations among the entities that make up the field as a whole. In decentralized networks, this includes everyone involved in investing, building, operating, using, or otherwise participating in the network. Governance is a process embedded in the structure of the network, initially determined by the entities closest to its launch. Subsequent actions by network participants either reinforce or challenge the existing structure, while increasing or decreasing the amount and value of the resources available. The structural evolution of a network is strongly affected by the social norms and rules of the network, including those specified in relevant software protocols. As a result, the power to legitimately (re)define these norms and rules is one of the key stakes in network politics.
3. In addition to conventional market dynamics, an overarching factor driving the evolution of decentralized networks is the tension between ideology, reality, and financial incentives.
Despite their many differences of opinion in specific areas, people participating in blockchain networks tend to share certain ideological or pragmatic dispositions, expressed in concepts such as decentralization (resilience against collusion and minimization of single points of control or failure), self-sovereignty (individual freedom, ownership, and privacy), permissionless access, censorship-resistance, open source software, and criticism towards excessive intermediation or rent-seeking. However, what’s ideologically preferable is not always technically or sociologically realistic. Blockchain innovators are constantly threading the needle between the two, trying to avoid reproducing problems that their innovations are intended to solve — a task that is made more arduous by the influence of short-term financial incentives. The economic success or mass adoption of individual networks is not necessarily dependent on strict adherence to some narrow set of principles. But the interplay between ideology, reality, and financial incentives will remain a key influence on how systems of network governance are designed and evolve.
4. Decentralized network governance consists of four main components: (1) leadership, vision, and values that attract and guide network participants; (2) rules inscribed in the relevant software protocols; (3) rules and regulations external to the relevant software protocols; (4) community coordination and management.
The initial vision and values behind a particular network are expressed in founding documents, details of network launch, and the personal views and preferences of early contributors. Software protocols are used to define how the network handles the most important information and transactions, which may include rules on implementing changes to the software itself, known as on-chain governance. Additional rules may emerge independently of the software, mainly through organizations that help coordinate the activities of the broader community, known as off-chain governance, which often resembles the governance of traditional free and open source software (FOSS) projects. The most innovative aspects of decentralized network governance are found in the on-chain component, especially as it relates to on-chain data analytics, tokenization, automation, and novel forms of online voting, which usually focus on software updates or the distribution of common pools of financial resources.
5. Existing systems of decentralized network governance differ in two defining aspects: (1) whether rules around implementing changes to the relevant software protocols are included in the software itself; (2) the level of formalization and institutionalization of off-chain governance.
Software protocols running on decentralized networks are subject to both planned and emergency updates. Network participants are generally free to choose whether to interact with the software or not, and thereby continue participating in or leave the network. Networks differ in the degree to which the software itself is used to formalize and automate the coordination and decision-making that guides the system (the relative importance of on-chain governance), which may include a voting mechanism tied to an identity verification process or a network-specific token. While on-chain governance is formalized by definition, off-chain governing activities are spread across a spectrum from more informal and irregular to increasingly institutionalized. Off-chain governance includes uncoordinated individual action, private conversations, public events, online interactions (especially on social media platforms where materials and memes are circulated), activities of various legal entities contributing to the network, as well as voting and decision-making mechanisms independent of on-chain governance.
6. Avoiding changes to software or other system parameters helps preserve existing systemic tendencies; changing software or other system parameters may introduce new risk factors, but is also a powerful tool for enabling new systemic tendencies.
Reducing the perceived need and legitimate options for changing the rules of the network is often referred to as governance-minimization. In practice, it amounts to (1) the ossification of early design choices (i.e. maximizing the discretion of individuals who performed one of the most important acts of decentralized network governance by defining the initial rules of the system), or (2) increasing the system’s ability to adjust to changing circumstances automatically (i.e. with minimal human effort). In such networks, considerable effort is often spent on defending the immutability of the design features and control mechanisms that govern the system. While a strong bias for maintaining the status quo or strict adherence to a specific set of rules could hinder the network’s ability to evolve and improve, it helps preserve existing systemic features and tendencies. In contrast, more open-ended and dynamic systems of governance tend to be less stable but also more adaptable. By providing legitimate options for different stakeholders to affect the rules, structure, and direction of the network in reaction to changing perceptions or circumstances, such networks are better positioned to address systemic issues, but thereby also more likely to introduce novel risks and challenges.
7. Good decentralized network governance is one that steers the network through its various stages of development towards more innovative and socially useful functions, while adequately resolving conflicts between different stakeholders participating in or affected by the network.
Humans avoid the need to constantly renegotiate solutions to recurring problems by developing habits and roles that eventually become institutionalized — a manual equivalent of rules-based automation. But even the simplest and most stable institutions are embedded in a complex and constantly changing environment. As a result, institutions need to adapt and evolve, which can be difficult due to conformism, structural inertia, and the well-organized defense mechanisms of entrenched interests. The same applies to decentralized networks. Given the variation in founding principles and intended use, it is reasonable to develop different systems of governance for different networks. But generally speaking, good network governance aligns the interests of all stakeholders through a sufficiently flexible system of checks and balances. Imbalanced governance or inability to resolve conflicts between key stakeholders creates instability, which is particularly problematic for networks positioned to become systemically important administrative infrastructure with a very large user base.
8. In networks that adopt a formal system of governance, distributing decision-making authority among different stakeholders, including the end-users of the network, is an effective form of decentralization and a safeguard against the abuse of concentrated power.
Broadly speaking, the most important groups participating in decentralized networks are: (1) technical experts responsible for developing software and operating the relevant infrastructure (or otherwise contributing in a highly specialized capacity); (2) individuals and organizations with large financial interests tied to the network; and (3) users. In practice, there may be overlap between the three, but each is commonly associated with a particular form of decision-making: technocratic (experts), plutocratic (most financial skin in the game), and democratic (users at large). Decentralized networks tend to be technocratic by default. For more inclusive decision-making, a typical first step is to implement a token-weighted voting system, which usually results in a plutocracy. More democratic forms of network governance are currently underexplored and raise a number of difficult questions. Who or what defines the demos, the network constituency? Which decisions require a popular vote? Are there sufficiently secure and privacy-preserving voting solutions available? Assuming that some democratic check on the power of dominant actors is warranted, should it take the form of direct, representative, or delegative (liquid) democracy? These are all network-specific empirical questions.
9. The quality of non-expert decision-making in decentralized network governance is strongly influenced by political communication — a task that requires professionalization.
Most organizations that coordinate complex activities involving large numbers of people establish a division of labour, leading to the emergence of specialized stocks of knowledge and competence. Such specialization already exists in the design, building, operation, and governance of decentralized networks, and is likely to grow in the future. In networks where power is distributed among individuals who are not necessarily experts on matters they can influence, it therefore becomes necessary to inform the constituency about the potential effects of their decisions and the relative merits of competing paths forward. This is the world of network politics, where different stakeholders — often via charismatic individuals with good communication skills — seek popular support for their ideas and plans. Beyond their role as passive consumers, the vast majority of users are unlikely to participate in the more technical or everyday aspects of network governance, especially when they’re content with the status quo. But this should not be construed as sufficient evidence against the benefits of empowering end-users, such as encouraging public debate, accountability, and legitimacy, all of which are particularly important in times of contention or crisis.
10. Decentralized networks with governance models that are poorly defined or overly complex and resource-intensive tend to be at a long-term disadvantage relative to competing networks that optimize for procedural clarity, simplicity, and smart automation with emergency safeguards.
Opaque and inconsistent governance models make it difficult for network participants to coordinate around a shared understanding of what’s a legitimate course of action in different situations. This increases the likelihood of conflict, which may lead to fragmentation and network forks. Networks with governance models that are too complex or require excessive amounts of human effort or other resources tend to be less scalable and less adaptable than networks with governance models that combine simple design principles with an ability to manage change when necessary. A popular method for making the governance of decentralized networks more efficient is automation — any technique that reduces the need for human assistance in performing a task or completing a process. However, automated governance mechanisms should be continuously assessed based on the systemic tendencies these mechanisms promote, and augmented with appropriate safeguards for handling emergency situations caused by catastrophic software bugs or other extreme events.