This piece covers the historical context to better understand what is a DAO, where did the idea originate, and what are the underlying tensions in algorithmic governance surfacing in DAOs.
What is being organized, what is being decentralized, and who, or what, are being made autonomous in “Decentralized, Autonomous, Organizations”?
Suggested citation (original full-length article, including links to references): Nabben, K. "Experiments in algorithmic governance continue: Trying not to fail at Decentralised Autonomous Organisations (DAOs)”. Substack. 29 July, 2021. Available online: Experiments in algorithmic governance continue - by Kelsie Nabben - Kelsie - on the cataclysmia of digital infrastructure.
“Decentralized Autonomous Organizations” (DAOs) are a revolutionary way of self-organizing, dreamed in the tradition of the dominant libertarian imaginaries of the cypherpunks, where governance is administered by software code in a network of people. Blockchain-based tools are at the stage where they are mature enough to support rapid experimentation regarding this concept. DAOs are often promised to be participatory, highly democratic systems that offer operational efficiency. DAOs are socio-technical hybrids, that operate in both the “on-chain” and “off-chain” world. The nature of these systems is still emergent, and the human outcomes of these systems remain understudied.
What is a DAO?
The history of modern-day DAOs in the blockchain space
The tensions between the role of humans and algorithms in autonomous systems
DAO governance approaches as social and technical (“on-chain” and “off-chain”)
Modern day DAOs
Process to get to DAO (DAO First or “exit to DAO”)
Qualitative, ethnographic research, comprised of ethnographic interviews, digital ethnography, and case study analysis.
This blog outlines key historical and cultural dynamics of DAOs, especially the tension between human and algorithmic influence in DAO governance. I outline the history of the modern blockchain community concept of DAOs, the tension between human and algorithmic components in DAO governance as steeped in “on-chain” and “off-chain” governance debates, and some common approaches to establishing a DAO, which are useful delineations for later case studies.
This establishes a basic DAO lexicon by which to observe the elements and categories of DAOs against certain vulnerabilities to observe and understand resilience in DAOs as examples of attempts at political decentralization via algorithmic governance.
“Decentralized Autonomous Organizations” (DAOs) are a new form of politically decentralized organizations that promise “autonomy”. In 2017, Quinn DuPont authored a book chapter on “Experiments in algorithmic governance: A history and ethnography of “The DAO,” a failed decentralized autonomous organization” (2017). Yet, these experiments continue.
“Decentralized Autonomous Organizations” (DAOs) are a revolutionary way of self-organizing, dreamed in the tradition of the dominant libertarian imaginaries of the cypherpunks, where governance is administered by software code in a network of people. Blockchain-based tools are at the stage where they are mature enough to support rapid experimentation regarding this concept. DAOs are often promised to be participatory, highly democratic systems that offer operational efficiency (Wright, 2021). DAOs are socio-technical hybrids, that operate in both the “on-chain” and “off-chain” world. The nature of these systems is still emergent, and the human outcomes of these systems remains understudied. This piece explores the question, “are DAOs resilient?” in relation to notions of “autonomy” and automation through algorithmic governance.
In my studies of resilience in decentralized technology communities, I argue that resilience is the ability of a socio-technical system to adapt and transform in response to threat or crisis. In DAOs, resilience is the ability of the DAO to persist in response to social or technical attacks or shocks (Nabben, 2021). I observe vulnerabilities as a relational notion to resilience in order to study socio-technical systems. I approach governance as the field of action for coordination and control of a complex system. DAOs, require establishing the field of action (initial settings), as well as the technical, social, and cryptoeconomic actions possible.
What is a DAO?
The acronym “DAO” stands for “Decentralized Autonomous Organization”. The initial, basic purpose of a DAO is that of a virtual entity where members have the right to spend funds and modify code. Although there is no formal definition of a DAO as these institutional forms are still evolving, a DAO is a model for coordinating amongst peers with no central intermediary, towards a stated objective.
In 2013, co-founder of Bitshares, Steem, and EOS blockchain Dan Larimer described Bitcoin as a type of DAO, using the metaphor of cryptocurrencies as shares in a “Decentralized Autonomous Corporation” (DAC) with the goal of earning profit for shareholders by providing services on the free market. Five days later, then author at Bitcoin Magazine Vitalik Buterin (now founder of the Ethereum blockchain), pointed out that corporations are “nothing more than people and contracts all the way down” (2013).
The concept of DAOs has since been popularized by blockchain communities, especially in the Ethereum ecosystem. The software language of the Ethereum protocol allows automated, smart contracts for the enactment of composable governance processes and mechanism, and DAOs are proliferating as an open field of experimentation in automation, governance, and autonomy. DAOs have been referred to as a site of algorithmic governance for further ethnographic enquiry (DuPont, 2017).
The history & purpose of “Decentralized, Autonomous, Organizations”
Decentralized Autonomous Organizations enable things to be organized in a politically decentralized manner (Buterin, 2017). “Decentralized” refers to architectural decentralization of physical computing hardware, or “nodes” in the peer-to-peer network, as well as freedom from coercive authorities or intermediaries that may hold power to influence a system.
“Autonomous” refers to independence, or self-governance of individuals and the organization itself. This is not be not to be confused with automated, although the automatic execution of rules leads to autonomy (Voshmgir, Zargham, Emmett ,2021). According to Buterin, the idea of autonomous systems pre-dates blockchain communities (see Robin Hanson’s futarchy, “a mechanism for organizational governance via prediction markets”, “automaton” self-operating machines, and the novel series Daemon (2016).
DAOs are a continuation (the logical extension) of the cypherpunk ideal of cyber and physical autonomy. The cypherpunks deeply explored ideas of automated, digital markets and physical world outcomes in the 1990s, in the lead up to the invention of Bitcoin. Some even advocated for the abolition of property rights and creation of “Temporary Autonomous Zones”, of ad hoc, self-governing territories of non-hierarchical social systems that “elude formal structures of control” (Bey, 2008). DAOs operate in digital space but extend to influence the physical world.
In 2014, Buterin describes that “instead of a hierarchical structure managed by a set of humans interacting in person and controlling property via the legal system, a decentralized organization involves a set of humans interacting with each other according to a protocol specified in code, and enforced on the blockchain.” While these ideas existing in business, economics, cybernetics, and politics prior to the open-source blockchain communities of today, decentralized, public blockchains make them possible.
One way to analyze DAOs is in terms of what is being organized, what is being decentralized, and who, or what, are being made autonomous? This includes whether autonomy is about individual autonomy, or collective autonomy, and what trade-offs are required to optimize for each.
The role of humans in autonomous organizations
The idea of DAOs is applicable to both corporations and communities. DAOs have internal capital (or property). The primary stakeholders of a DAO are investors, employees, and customers (Buterin, 2014).
The tension in decentralized governance that Buterin emphasizes is, how much do we really need people in algorithmically programmable organization? (2013). While some human action is necessary for higher order specialized tasks (not the other way around), people are increasingly less essential in the day-to-day operations of an organization in the post-industrial era.
“In an autonomous agent, there is no necessary specific human involvement at all; that is to say, while some degree of human effort might be necessary to build the hardware that the agent runs on, there is no need for any humans to exist that are aware of the agent’s existence.” — Vitalik Buterin, 2014.
The science fiction dream is that “autonomous agents” would-be actors, or stakeholders, in these organizations. A fully autonomous agent is the idea of fully Artificial General Intelligence (AGI). This encapsulates the very essence of resilience, in that the agent could adapt to circumstances, to transform and survive to meet its aims, into perpetuity. Observing attempts at “Decentralized Autonomous Organizations” reveals early dynamics of the social outcomes, benefits, and concerns, to hypothesize about the role of autonomous systems, and the possibility of autonomous agents, as coordination infrastructure.
DAOs “think” for themselves, with automation at the centre, and humans at the edges.
“ This vision stands in stark contrast to the state and corporate sponsored surveillance super-structures which are the primary applications of advancements in artificial intelligence funded and deployed by centralized institutions ” state Voshmgir, Zargham, & Emmett in “Conceptual Models for DAO2DAO Relations”, 2021.
Public decentralized blockchains, smart contracts, and the concept of DAOs provide the possibility to explore how much of an organization’s bylaws can be translated into software code and executed by smart contracts, to function autonomously from human direction.
What is being automated in blockchain institutions (such as DAOs) is some measure of trust in the system, to enable scalability of digital social institutions and the advancement of society. In the well-known essay titled “Money, blockchains, and social scalability”, Nick Szabo states that blockchains reduce human “vulnerabilities to our fellow participants, intermediaries, and outsiders”, which increases efficiency of resources and thus, social scalability (2017). “Trust minimization is reducing the vulnerability of participants to each other’s and to outsiders’ and intermediaries’ potential for harmful behavior” — Nick Szabo. DAOs intend to reduce human vulnerabilities, through blockchain enabled cryptographic trust minimization and automated efficiencies, to produce scalable, independent, self-directed social institutions and societies.
It remains to be seen whether individual and collective autonomy are indeed being enabled by these new, cyber-physical institutional forms. The next section will explore types of DAOs, the common approaches taken to create a DAO, as well as a definition of resilience in DAOs, for further case study analysis.
DAO governance: Technical on-chain and social off-chain
Scholars have referred to two main types of DAOs as participatory and algorithmic (Wright, 2021). Participatory DAOs are managed by distributed consensus through smart contracts to signal the preferences of members. Algorithmic DAOs aim to be entirely algorithmically governed, with the underlying smart contracts dictating the entire functionality of a DAO.
An example of a participatory DAO might be GitcoinDAO, which has a council of governors, which can allocate governance tokens to stewards, deliberates proposals on forums, votes on “Snapshot” (an “off-chain” voting tool), and then executed voted proposals, such as allocating funds. An example of an algorithmic DAO is DxDAO, which launched with no pre-defined members, and is completely community run without any intervention of a project or team, which controls a decentralized trading protocol and other DeFi tools. The aim of DxDAO, as well as other DAOs which may define themselves as “algorithmic”, is to be “as widely distributed as possible from day one”.
Yet, all DAOs are both participatory and algorithmic. This is what is unique about DAOs. DAOs require participation, which is a political process where the actors involved in decision-making processes are positioned towards each other through power relationships that occurs “off-chain”, and algorithmic governance, which is the point at which decisions are reflected and executed “on-chain” through the use of smart contracts. There is necessity and value in both the technical (including cryptographic and algorithmic) components of DAO structures and governance, and the social (including normative decision making, or decision making in line with cultural values of what is acceptable).
What this distinction in thinking between these two component points to is a much deeper cultural dynamic about the value and risks of social components versus the value of technical components in blockchain communities. This binary tension has repeated throughout blockchain history and is rooted in the history of blockchain governance.
A brief history of blockchain governance as “on-chain” and “off-chain”
Historically, blockchain governance refers to the rules among blockchain of how the software code of a blockchain protocol is changed. Ideas around blockchain governance are heavily embedded in culture, such as Bitcoin’s ideals of immutability, and minimal trust between people, which result in an ideology of “code is law” (Lessig, 2006). This debate about the role of people to intervene in algorithms is also referred to as “on-chain” versus “off-chain” governance.
“On-chain” governance is when governance rules are made explicit in software code, and blockchain nodes automatically execute code upgrades in the protocol in response to on-chain coin holders voting processes (Zamfir, 2017). In contrast, “off-chain” governance is when rules are much less formal, and the non-code-based processes of how ideas are shared, discussed, and evaluated outside of formal, recorded, transparent decisions are eventually reflected in nodes decisions upgrade their software to pass on changes to the protocol. Therefore, nodes in the peer-to-peer network are active participants in governance processes.
The premier example of the tension between algorithmic prominence, and normative (establishing norms, according to shared values) decision-making is “The DAO” hack. A bug in the code which allowed millions of dollars to be drained from the smart contract resulted in arguments in the community between whether it is right or wrong to change the record of transactions. This led to a “hard fork” of the Ethereum protocol, which established Ethereum and “Ethereum Classic”, as well as early Ethereum CTO Gavin Wood founded his own protocol known as “Polka Dot”.
In the aftermath of the hack and ongoing debates on governance, Buterin stated that “people who think that the purpose of blockchains is to completely expunge soft mushy human intuitions and feelings in favor of completely algorithmic governance (emphasis on “completely”) are absolutely crazy” (2017).
Today, the Ethereum community typically embraces its “off-chain”, human-oriented processes. For example, the Ethereum Foundation maintains an essential coordination role in the development of the protocol, such as hiring research and development staff and chairing regular “Ethereum Improvement Proposal” (EIP) meetings. The advantages of this approach were evident when the community needed to coordinate a rough social consensus of miners, exchanges, and node operators to upgrade their software to “fork” the protocol after “The DAO” hack. One disadvantage of a bias towards “off-chain” governance is mere efficiency and scalability, with the Founder of Ethereum Vitalik Buterin stating that the Ethereum2.0 protocol upgrade has been a significantly slower process than originally anticipated.
In contrast, other blockchain communities such as Polkadot and Tezos embrace on-chain governance, whereby protocol upgrades are determined through referendum type votes, and software code is immutable, meaning it cannot be changed once deployed. An advantage of this is representation and transparency. A drawback of this approach is to reduce governance to voting, when it is in fact multiple layers of social and technical components and processes interacting in the coordination and control of a system, which can’t be anticipated in advance, and are therefore impossible to encode into the rules of protocol in advance.
Blockchain communities orientate around the value of decentralization of political power. On-chain governance processes establish explicit rules of governance and offer transparency. In contrast, off-chain governance processes are opaque, messy, and inherently political, but in part unavoidable, and perhaps helpful, in leading, educating, and establishing clear and trusted direction in projects. The affordance given to social and technical aspects of governance in DAOs is not just a system design choice but an ideological choice. Participants in blockchain communities and governance develop cultural norms, which affect information and incentives (Zamfir, 2017).
It remains to be analyzed what outcomes and emphasis on “off-chain” or “on-chain” governance processes produces, and which is more resilient under certain circumstances.
“DAOism” — modern day DAOs
It’s safe to say that DAOs have become a “quasi-cyber-religion”.
Modern DAOs are commonly “decentralized applications” deployed on top of the layer 1 protocol blockchain (Hassan & De Filippi, 2020). The capabilities that public blockchains enable for experimentation with DAOs is evidenced by the plethora of approaches to “DAOs” popping up in blockchain communities today.
To obtain legal status as a registered corporate entity (in the US), a DAO must:
be deployed on a public blockchain,
provide a unique public address (has) so anyone can view their operations,
software code must be open-source, software code must be audited, laypeople able to read smart contract variables and token restrictions,
governance must be decentralized in the technical architecture of the DAO,
at least one DAO member,
a contact point,
a binding dispute resolution mechanism for participants, and,
a dispute resolution mechanism for interacting with third parties, outside of the DAO (Coala, 2021).
There are two simultaneous types of governance at play in blockchain infrastructure as a socio-technical systems: governance by the infrastructure and governance of the infrastructure ( De Filippi & Loveluck, 2016). This duality is evident in both the role and function of existing DAOs.
DAOs exist for venture capital allocation (FlamingoDAO), funding public goods (GitcoinDAO), managing “Decentralized Finance” (DeFi) protocol, such as Automated Market Makers (UniswapDAO), funding life extension research (VitaDAO), and building themselves (1Hive).
These can be further categorized, although definitions remain broad. DAO participants govern the rules of the protocol, as well as providing labour within the DAO, to be governed by the protocol.
Autonomy via composability
DAOs are developing towards the ideal of autonomy through the composable nature of blockchain infrastructure. A DAO, such as 1Hive, can run on a protocol, such as Ethereum. Unique identity can be verified through decentralized applications like BrightID. It can be publicly funded through a bonding curve, fair launch, or retroactive airdrop. Labour contributions can be recognized and measured in “cred”. Disputes can be arbitrated in decentralized courts through (such as Aragon or Kleros). And insurance can be supplied in the case of hacks or bugs in the code that lead to losses. These provide modular, composable, multi-layered mechanisms for executing specific governance processes that transition between physical space and cyberspace.
The next section outlines the common approaches to ‘creating’ or ‘becoming’ a DAO through the “DAOFirst” or “exit to DAO” approaches.
(Continue reading at the original post here: Experiments in algorithmic governance continue - by Kelsie Nabben - Kelsie - on the cataclysmia of digital infrastructure, and see links to references, of which there are many).
Constructive engagement on these ideas, examples of viable case studies, and links to other relevant resources on this topic are most welcome.
This is part 1, with a follow-up on specific case studies anticipated in the coming weeks.