Distributed Self-Government in Protocol Communities: An Introduction and Index of Examples.

AuthorBell, Tom W.
PositionReport

We live in exciting times for governance. Large and powerful institutions used to come in only a few standardized types, such as nation-states and commercial corporations. But the advent of distributed organizations, built on computer code and fueled by digital cash, has supercharged the evolution of social coordination systems. Richly capitalized global communities worth hundreds of billions of U.S. dollars now spring up seemingly overnight. They die just as quickly, too--taking high hopes and huge fortunes with them.

This article introduces newcomers to the fascinations of distributed-protocol communities and analyzes the self-governance of several of the largest and most innovative. It defines seven measures of governance and grades the performance of each of ten protocols on a scale of safe, caution, or danger. The resulting Distributed-Governance Index organizes and summarizes the latest developments in the evolution of distributed-protocol communities and provides a framework for continuing observation of this rapidly developing field. From these early efforts might come the next South Sea Bubble or the next best form of self-governance. It all bears watching at the least.

The first section reveals the origins, aims, and still brief but already turbulent history of distributed-protocol communities. The second section explains how the Distributed-Governance Index works--how protocols qualified for indexing, the scoring system, and a frank assessment of the project's limitations. The third section applies the seven performance measures, each in turn, to the ten protocols included in the index. The fourth section concludes with an overall analysis of the past and possible future of the self-governance of distributed-protocol communities.

Innovation in Distributed Governance

Legacy political institutions and businesses have never allowed the average person much direct influence over their operations. And until recently if you did not want to play by those rules, you could not very easily opt for new ones. It was too difficult to connect with counterparts, to reach agreement on better rules, and to decide on joint action. High transaction costs made serious governance--the kind that affects millions of people and billions of dollars--expensive, inefficient, and monolithic.

Now, though, you can enter into a new kind of government just by wiggling your fingers (and wading through some awkward interfaces). First, internet communications brought down the costs of finding and connecting people with shared interests. Then Bitcoin and other digital payment systems made it easier to store and transfer value. Today, communities such as Ethereum, EOS, and Dash offer protocols sophisticated enough to provide voting, delegation, funds disbursement, and other administrative functions. These distributed-protocol communities mark the farthest frontier of self-governance.

The largest of these new protocol-based communities host hundreds of billions of dollars in assets and make daily transactions worth millions of dollars. Anonymity and pseudonymity make an exact census impossible, but the networks can easily boast of having tens of millions of members scattered widely across the planet. Despite having so much at stake, though, these burgeoning communities have thus tar struggled to govern themselves well. Even the most successful of them have suffered embarrassing failures, such as hacking attacks, unplanned hard forks, and ad hoc control by connected insiders. Such stumbles have discouraged investment and encouraged skepticism about cryptoeconomics.

Market commentators have begun to notice the importance of governance in their assessments of the risk/return profiles of cryptocurrencies (S+C Intelligence 2019). Developers of newer and presumably more advanced protocols trumpet their devotion to the concept (Dash Core Group Inc. 2018; EOSIO 2018; Decred Developers n.d.; Horizen n.d.; Tezos Foundation n.d.). It remains unclear, however, whether more governance means better performance. The spectacular returns generated by Bitcoin, the cryptoanarchic original, suggests ... perhaps not. The kind of governance evidently matters, too. But what kind? Until now, commentators could only watch and wait to see which fledgling protocols would survive the brutally uncaring market.

Though these fledgling organizations have no trouble qualifying as communities, they fall short of having a huge impact on the everyday lives of everyday people. Even so, the billions of dollars in assets and millions of daily transactions hosted by leading distributed-protocol communities shows that this is no mere computer game. And to take them at their word, the leading proponents of distributed-protocol communities want such communities to take over the world (Bell forthcoming).

The Distributed-Governance Index (DGI) set forth in this article offers a framework for understanding this recent explosion in new kinds of government. It documents and compares the performance of the largest and most interesting protocol-based communities in several key areas, such as exposure to 51 percent attacks and funding for shared infrastructure. Table 1 summarizes the results. Its shade-coded assessment, with darker grays corresponding to greater danger, offers a quick look at how each of the indexed protocols fares under each of the variables, explained more fully later, that track the self-governance of these communities.

Table 1 necessarily omits many crucial details. Most notably, it does not indicate which variables matter the most. (The columns have equal width for mere aesthetics--not to indicate the relative importance of each variable.) Some readers might regard a protocol's susceptibility to 51 percent attacks, an existential risk, as far more important than other considerations of good governance. Other readers might care more about protecting a community from infections of liability-inducing data. The novelty of these questions counsels against the DGI taking a decisive stance on the relative importance of the variables it tracks. It reports, you interpret, and fate decides.

The rest of this article explains the DGI's methodology, analyzes the performance of the protocols under each of several variables, and summarizes what these findings suggest for best practices in distributed governance. Governance represents one of the hoariest of human problems. Distributed protocols represent a new and largely untested technology. What happens when they collide? This article can only begin to study this newest example of human sociability. It cannot tell exactly where any given protocol's form of self-governance will lead that protocol, of course. Nor can it say exacdy where this ferment in self-governance will lead. But it does say: keep watching distributed governance.

Methodology of the Distributed-Governance Index

This section examines what qualifies protocols for inclusion in the DGI and how the index deals with the variables of governance that it tracks.

The DGI focuses on the biggest distributed protocols, measured in terms of the market capitalization of their associated cryptocurrencies. Capitalization serves as a rough but fair first pass for finding the most promising candidates because it indicates that investors do not regard a protocol as utterly incompetent or dishonest--at least not in the short term. The DGI also considers a select few other protocols that include good government among their express goals. Table 2 cites the protocols and their putative internet homes. The top six were chosen solely by merit of their leading market capitalizations. The bottom four were chosen for their expressed interest in governance. All data come from CoinMarketCap (2019).

Market capitalization and self-identification do no more than determine which protocols get into the DGI. To make more accurate and longer-term assessments of governance, the index combines a number of measures of a protocol-based community's institutional health. It is not easy to assess how well a network will operate in practice simply by reading its white papers. Not even going over its supporting code with a fine-toothed comb would identify flaws in the system's incentive structure. Market capitalization and transaction volumes, although important markers of vital functions, might reflect artificial stimulation. And even when a network attracts users the honest way, latent systemic defects can destroy it all.

Like a physician conducting an overall physical exam, the DGI examines a number of markers of good governance. None of these admits to direct quantitative measurement. The index instead relies on informed expert opinion to assess each variable under consideration. Like traffic signals, these shade-coded scores indicate assessments of danger, marked in a dark 35 percent gray, caution in a medium 20 percent gray, and safe in a light 5 percent gray. Although rough, these methods will have to suffice pending more direct, objective, and refined measures of governance.

THE INDEPENDENT REVIEW

The DGI tracks seven variables:

* Exposure to 51 percent attacks

* Chain-cleaning mechanisms

* Secret-voting options

* Open access to proposals for improvements

* Processes for amending the protocol from within

* Systems for funding common goods

* Users placed in privity of contract

Details about each of these variables are given in the third section.

Notably, the DGI does not quantify the relative importance of these variables in providing good governance. Some variables doubtless matter more, granted, as suggested by the order in which the index addresses them. But it would brook hubris to take a firm stand on that ranking, much less to assign numbers to each variable. By similar token, though its danger-caution-safe scores could easily admit to some kind of numerical interpretation, the DGI does not pretend that its subject--the collective behavior of humans and machines experiencing...

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