Decentralized Network Governance

* Article: Decentralized Network Governance: Blockchain Technology and the Future of Regulation. By Andrej Zwitter and Jilles Hazenberg. Blockchain for Good, 2022.

URL = https://www.frontiersin.org/journals/blockchain/articles/10.3389/fbloc.2020.00012/full

Definition

By Andrej Zwitter and Jilles Hazenberg:

"Within the digital domain, and more specifically the domain of digital network providers, the state has limited powers and new actors emerge. These new actors command others through network-making and networked power, in a multitude of continuously changing relationships. Individual ownership of governance is limited. Governance over and within this network is thereby differentiated. This problematizes that power is dispersed throughout the network and is dependent on clusters/alliances of actors that can change per topic."

(https://www.frontiersin.org/journals/blockchain/articles/10.3389/fbloc.2020.00012/full)

Description

By Andrej Zwitter and Jilles Hazenberg:

1.

"This paper reviews the literature on governance theory in order to conceptualize governance as a mode of decentralized, networked regulation. We argue that the current dominant modes of governance are inadequate in understanding governance in the digital domain and are poorly equipped to conceptualize novel forms of governance such as decentralized autonomous organizations (DAOs). Therefore, this study proposes a new mode of governance based on the regulation of new power relationships between the state and actors in the digital domain. This model further explores the role that blockchain technology can play in what we term decentralized network governance."

2.

"This paper consists of four sections.

• In the first section, the terms datafication and blockchain technology are introduced.

• In the second section, governance literature is reviewed and dominant modes of governance are conceptualized.

• In the third section, arguments are put forward concerning why these modes of governance are inadequate in terms of effectively governing the quasi-theoretical conceptions introduced by DLT and blockchain technology.

• The fourth section offers the first methodological clues for the analysis of network governance, based on social network analysis.

These methods will allow for better decisions to be made regarding how to design and disseminate power relationships into technological solutions, which require oversight and regulation."

(https://www.frontiersin.org/journals/blockchain/articles/10.3389/fbloc.2020.00012/full)

Typology

By Andrej Zwitter and Jilles Hazenberg:

1. Forms of networked power:

"• Networking power: the power that actors and organizations have that constitutes the core of the network. This power pertains to the ability to include and exclude others, and thereby controls the makeup of the network.

• Network power: the power that results from the standards required to coordinate interactions. This primarily concerns the imposition of rules within a network.

• Networked power: the power that actors have over one another within a network. This power mimics traditional conceptions of power but the way in which it is exerted differs per network.

• Network-making power: the power of an actor or organization to constitute or re-program a network according to its values and specific interests."

(https://www.frontiersin.org/journals/blockchain/articles/10.3389/fbloc.2020.00012/full)

2.

"Within governance literature, Mode 2 governance is sometimes depicted as “network governance.” Within this strain of governance literature, the “network” is employed primarily as metaphor to exemplify the increasingly horizontal structures of Mode 2 governance and mechanisms of compromise and negotiation. We refer to decentralized network governance as the governance of a network (e.g., a blockchain network) through a network (the multiplicity of actors that exert power in continuously changing roles and relationships). Moreover, literature that describes Mode 2 governance as “network governance” often focuses on the relationships and mechanisms of coordination within institutions, for instance, regulatory agencies or public administrations. The present conceptualization does not confine itself to such a limitation. See Klijn (2008); Koppenjan and Klijn (2004), and Lewis (2011).

Manuel Castells conceptualizes networked power as the dominant form of power exerted within modern networked societies. This is not the time or place to argue for or against this conceptualization of societal powers that structure modern societies. We employ these forms of network power as they directly relate to new powers that emerge within networks. The cyber domain is thus conceived as network, and its most prominent exemplifications are literally so without necessarily conceiving of societies themselves as networks.

Characteristics

By Andrej Zwitter and Jilles Hazenberg:

"Logically, three strategies of decentralized network governance can be conceptualized:

(1) Platform strategy, in which crowds, e.g., interest groups or one-issue parties, are enabled by the state (off-chain) to critique and protest about powerful actors within the network (on-chain). In this role, the state can also facilitate the education of under-informed individuals and institutions.

(2) Private strategy, in which crowds cooperate within a network to achieve certain goals, put certain proposals forward, or correct and counterbalance other power brokers in the network.

(3) Legal strategy, in which the state or the designer of a technology, e.g., the DAO with regard to blockchain technologies, enables actors to effectively protest against and critique powerful actors. This is done by exempting them from legal requirements when there are grave power imbalances in specific relationships.

The common effect of these strategies is that they enable deliberation among the relevant actors and allow weaker actors to join forces to counterbalance more powerful ones. In a context where traditional governance fails, decentralized network governance opens up a space for contestation in which actors in concert govern each other. The available means range from educational pursuits to legalizing otherwise illegal means such as white-hat hacking or other forms of protest. Such governance has the best chances to achieve effective regulation of power relationships and can trigger increased and better self-regulation. This can be done, for instance, by motivating powerful actors to initiate more detailed codes of conduct in concert with societal actors, or by improving international public collaboration regarding the protections of rights for weaker parties in the digital domain."

(https://www.frontiersin.org/journals/blockchain/articles/10.3389/fbloc.2020.00012/full)

The 'Clustering Coefficient'

"Of particular utility for decentralized network governance is the clustering coefficient. Defined in social network theory, this measure concerns the degree to which actors in a social or policy network cluster together. It is based on the empirical finding that, in social networks, members of distinct groups share a more tight-knit network among each other. Within a network, distinct groups are thus characterized by a high density of ties among a set of nodes. The clustering coefficient can be used to identify groups within a larger digital network that were previously unknown and that might either leverage their coordinated power vis-à-vis the rest of the network, or provide specific services. For example:

“Core Ethereum developers were in favor for such a hard-fork in order to return stolen funds. Most miners followed their lead. However, a minority of miners rejected the controversial idea to change immutable transactions and continued mining the old blockchain. This divided Ethereum into two co-existing blockchains, the new one, Ethereum (ETH), and the old one, Ethereum Classic (ETC).” (Friebe, 2017)

This illustrates that while technically everybody has an independent vote, the leverage of prestige and networking power (see Castells’s classification above) can determine the outcome of off-chain voting and have direct on-chain effects as the split into two Ethereum blockchains illustrates. At the same time, increasingly larger mining pools are being established in order to share processing power and, thus, the mined benefits. Furthermore, we are increasingly witnessing single private-sector actors establishing themselves in various blockchain domains by using large server farms, in order to maximize profit. These developments indicate that centralization and clustering are taking place, which requires further analysis and potentially governance mechanisms to regulate their effect.

In addition to the three strategies of decentralized network governance mentioned in the previous section, the brokerage positions within policy networks in particular can be leveraged to achieve desired outcomes or to avoid undesired ones. Brokerage positions appear when we have a look at different groups in the policy network. According to Gould and Fernandez (1989), actors can:

(1) coordinate within a group (coordinator),

(2) consult members of a group as an outsider (consultant),

(3) prevent or facilitate outsiders to gain access to a group (gatekeeper),

(4) represent the group to the outside (representative), or

(5) mediate between separate groups (liaison).

As illustrated above, network theory and its methodical application through social network analysis can, thus, provide concrete insights into existing blockchain and DLT applications. This methodology can be applied to both on-chain and off-chain dynamics. It can also be used to design smarter digital networks and assign roles to actors depending on their centrality and brokerage positions, as well as identify groups within a larger network that can fulfill certain functions (such as counterbalancing powerful single actors). Methodologically, social network analysis might have a central role to play in the further development of a theoretical framework regarding decentralized network governance. Ultimately, this may help contribute toward the effective governance of the digital domain."

(https://www.frontiersin.org/journals/blockchain/articles/10.3389/fbloc.2020.00012/full)

Excerpt

From the conclusion:

"Over the years, governance mechanisms have adapted due to globalization, increased technical specialization, and functional differentiation. However, governance also needs to adapt to the technical innovations of the digital domain in general, and to the increasing use of blockchain technology in particular. Due to the use of and reliance on digital networks, DLT and blockchain technology are increasingly shaping our societies and power relationships. Even at a time when their full potential is still debated and undetermined, the effects of technologies as governance instruments are increasingly tangible. In the present article, we have provided the first systematic steps toward the necessary reconceptualization of governance as applicable to societies increasingly shaped by digital networks and blockchain technology. We have proposed a framework of decentralized network governance. As illustrated in this paper with cases from blockchain technology, decentralized network governance is by no means limited to DLT. It applies equally to all modern power relationships that are characterized by the preponderance of private actors that provide networks of communication for other private actors.

In order to set the stage and explain the necessity of a reconceptualization of governance, we started by outlining the transformative nature of blockchain technology as a case within and representative of the larger implications of the changes experienced in the digital and online domain. It became apparent that DLT has concrete, disruptive effects on policy-making when examining the impact on existing actors and the emergence of new ones. Furthermore, for the purpose of developing a stringent framework for decentralized network governance, old (Mode 1) and new (Mode 2) governance were analyzed, focusing on power, identity, and the roles that actors play within these forms of governance. Mode 1 describes traditional, hierarchical governance with fixed identities (states, corporations, and citizens).

Mode 2 describes a more horizontal form of governance with fixed roles depending on power and expertise. Within Mode 2 governance, one can identify three forms: (a) public–private governance, (b) non-autonomous self-governance, and (c) autonomous self-governance.

To illustrate this, we took blockchain technologies and DAOs specifically as examples. We concluded that these examples are inaccessible to both traditional forms of governance. The core critique is that both modes of governance do not take into account the fact that the roles of actors in DLT-based solutions are constantly changing, and that power is context-specific and relational. This became apparent in the off-chain solution sought to remedy the DAO hack. In order to capture this new form of governance, which is also applicable in all sorts of digital networks, we propose the concept of decentralized network governance. This new mode of governance is characterized by the changing and multiple roles of actors, and the necessity to identify roles depending on network clusters and policy domains. This new perspective on governance as networked but decentralized opens up new policy mechanisms such as the design of new platforms for counterbalancing emergent digital actors. Network-making power facilitates the provision of such platforms for interest groups, tech-brokers, and private citizens, as well as actors with weaker power. Whereas on-chain governance can impose a mode of governance explicitly, off-chain governance can assume such governance structures tacitly. This governance structure in technology networks displays the fluid features that characterize decentralized network governance.

It would have gone beyond the scope of this article to further unearth empirical material in the blockchain domain to flesh out the theoretical framework presented here. Therefore, it would be worthwhile to further investigate whether the interaction between on-chain and off-chain governance does indeed lead to specific governance dynamics. If the future of governance is indeed one of changing roles and power alliances, we should expect to see increasingly fluid dynamics within and surrounding digital networks. Such fluidity could express itself merely as users of the network banding together and increasingly defining the network. It could, however, also take explicit forms of governance within set rules of the network. This would depend on whether the network allowed for such decisions itself (e.g., on-chain) or whether it required extraordinary measures to be taken outside the network (e.g., off-chain, or alternative platforms).

Hence, decentralized network governance, as a new Mode 3 governance, allows for the conceptualization of new forms of regulation of digitalized social affairs. This is illustrated by the multiple uses of blockchain for logistic, financial or contractual purposes, which acknowledge the fluidity of roles of actors in and around blockchain networks. It recognizes that traditional means of command-and-control governance have little use concerning radically democratized platforms. This conception of a third form of decentralized, yet networked, governance gives concrete indications of the utility of social network analysis with regard to policy-making and the design of governance tools in the digital domain."

(https://www.frontiersin.org/journals/blockchain/articles/10.3389/fbloc.2020.00012/full)