DAO Governance Mechanisms 101: How Web3 Communities Make Decisions

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As the Web3 industry continues to mature, governance is emerging as one of the most crucial components of their long-term success. In traditional systems, governance adopts a top down approach, whereby the majority of the decision-making power is managed by central authorities. But the ethos of Web3 is decentralisation, and in decentralised networks, value, identity and decision-making are distributed, ergo governance needs to evolve. Now you may be asking yourself, what are governance mechanisms?

Put simply, governance mechanisms are the methods or systems that communities use to come to decisions. In the context of Web3 or crypto, they are essentially the tools that allow distributed groups of people such as token holders or DAO members to vote, propose or agree on changes, such as how to spend treasury funds, upgrade a protocol or elect representatives. All these different types of governance mechanisms may vary in complexity and intention, but they all have the purpose of enabling decentralised communities to coordinate effectively. Now, let's explore some of the most widely adopted governance mechanisms, their nuances and their real world impact where applicable.

1 Token, 1 Vote Mechanism

One of the most common governance models in web3 is the “1 token, 1 vote” system, where each governance token is representative of a single vote. In this model, a user's voting power is directly proportional to the number of tokens they hold at the time. For example, an individual holding 1000 UNI tokens would have 1000 votes.

This approach offers several advantages, including simplicity, as it is relatively straightforward to implement and easy for participants to understand. Additionally, this model aids in aligning incentives through giving greater influence to those who are most financially invested in the protocol.

However, this model has its disadvantages. It carries the risk of creating a plutocratic system in which large token holders, such as well-funded entities or whales, can dominate decision-making processes. This concentration of power mitigates the influence of small token holders, reducing the democratic nature of the system. Despite these drawbacks, the one token, one vote mechanism remains widely adopted across the web3 space, with most DeFi protocols and DAOs adopting this model, or a variation of it.

Stake-Weighted Voting

A slight variation on the previous model is stake-weighted voting. Instead of merely owning tokens, participants must stake them to gain voting rights. The more tokens one has locked up, the more influence you have in the decision-making process. The logic here is that those who are willing to commit capital to the system are more likely to act in a fair and honest manner, aligning with the protocol’s long term interest.

However, this model is not without vulnerabilities. Flash loan attacks, such as the one that hit bZx Protocol, are a stark reminder of how easy it is for malicious actors to temporarily borrow tokens and swing a vote. Interestingly enough, BZx Protocol was a victim of flash loan attacks, not just once, but twice!

Other risks include whale domination, where large token holders and/or coordinated groups can dominate votes to push self-serving proposals. In addition, bribe attacks can seriously undermine governance integrity, as participants are financially incentivised to support certain proposals, prioritizing personal gain over community outcomes. A clear example of this was during the Curve Wars, where various projects offered rewards to veCRV holders in exchange for favourable votes, distorting the fairness of the process.

While stake-weighted voting offers an incentive-aligned approach to governance, these vulnerabilities highlight the need for complementary safeguards to mitigate against manipulation whilst also preserving trust within decentralized ecosystems..

Quorum Voting

Beyond who gets to vote, there’s also the question of how many people need to vote for a decision to be valid. This is where quorum voting comes into play. It sets a minimum participation threshold i.e. a quorum, that must be met for any proposal to pass.

The intention of this model is to prevent small, unrepresentative groups from making big decisions, whilst also maintaining legitimacy by only approving proposals that generate sufficient community interest and active participation.

However, quorum voting does have its challenges. If quorum thresholds are set too high, it can lead to governance paralysis, where achieving the necessary participation threshold becomes difficult, ergo decision-making stalls. Additionally, individuals may purposely remain inactive with the intention of sabotaging potential proposals being passed. Members with more tokens have the potential to manipulate and bribe others, going against the democratic, equitable nature of DAOs.

Quadratic Voting

To go beyond simple yes-or-no answers and flat vote counts, some communities have opted to quadratic voting. This system allows users to cast multiple votes on a proposal, but each additional vote costs exponentially more. In theory, it allows users to express their strength of support, not just what they support.

For example; casting one vote may cost one credit, two votes four credits and three votes costing 9 credits. An individual given 16 credits, may allocate 9 of their credits (3 votes) to support a single project they feel passionately about, whereas another individual may split their credits evenly across multiple projects.

Gitcoin Grants utilizes Quadratic Funding (QF), a mechanism closely related to QV, to allocate funds to open-source projects. In QF, the number of unique contributors significantly influences the matching funds a project receives, helping to strike a balance between broad community support with the intensity of support

The quadratic voting mechanism offers several benefits, such as mitigating the dominance of wealthy participants through making it increasingly difficult and expensive to concentrate voting power, thus helping promote a more equitable governance system. However, there is potential complexity for novel users who are unfamiliar with such a system. Additionally, if fake identities participate in the voting process, it can distort the results.

Pairwise Voting

In situations where multiple proposals are competing, pairwise voting offers an alternative approach. Pairwise voting is a governance mechanism in which voters compare proposals directly against one another through a series of head-to-head matchups. Instead of evaluating all options at once, participants elect their preferred proposal from each pair, and the process continues as each winner advances to face other winning proposals. Similar to how a knock-out tournament would work. This iterative process repeats until an overall winner is identified.

Because pairwise voting requires direct comparisons between proposals, it becomes increasingly difficult for large token holders (whales) to dominate the process, fostering a more equitable outcome. However, the system is susceptible to Sybil attacks, where bad actors can create multiple fake identities to manipulate outcomes. Additionally, proposal flooding is a possibility, whereby a number of proposals can actually dilute attention and votes. Despite these risks, pairwise voting still remains a viable tool in Web3 governance.

Conviction Voting

Conviction voting introduces a time component to governance. Instead of casting votes all at once, participants continuously stake tokens on proposals they support, with their voting power referred to as "conviction" growing over time as tokens remain locked. Once a proposal's conviction surpasses a predefined threshold, it is automatically approved, eliminating the need for fixed voting periods.

For example; a proposal requesting 10,000 tokens to fund a community event might initially attract 5,000 tokens staked by supporters. As time progresses, the total conviction increases, this is calculated by multiplying the number of staked tokens by the duration (time) they’ve been committed (staked) until it crosses the required 10,000 token threshold, triggering approval.

This system brings several advantages: it rewards long-term commitment, reduces the impact of short-term manipulation, and allows proposals to pass as soon as they gather enough sustained support. On the other hand, such a system also introduces specific vulnerabilities. Whale conviction capture occurs when a large token holder stakes heavily early on, making it difficult for others to intervene before the proposal is approved.

Other risks include malicious proposal farming, where attackers flood the system with low-quality proposals to dilute attention, and rage quit conviction drain, in which an attacker withdraws support just before execution, destabilizing the system. Conviction leasing attacks are another threat, particularly in ecosystems that allow token renting, enabling malicious actors to temporarily acquire enough tokens to pass harmful proposals.

Despite its flaws, conviction voting remains an innovative model for proposals that may need time to gain support and mature organically.

Ranked Choice Voting (RCV)

In the scenario where there are multiple competing proposals on the table, ranking them by preference offers a way to capture community sentiment whilst avoiding the pitfalls of vote splitting. Ranked Choice Voting (RCV) enables participants to order proposals based on their priorities, allowing outcomes that better reflect the collective will of the group.

For example, a DAO allocating treasury funds might consider three options: upgrading infrastructure, launching a new grant program, and hosting a community event. Members assign first, second, and third-place rankings to these proposals, ensuring the final decision accounts for a broader range of preferences rather than relying solely on a simple majority.

RCV brings several advantages. Firstly, It helps prevent similar proposals from dividing support, leading to more representative results. Members can express more than just their top choice, which is especially valuable in communities managing diverse needs like treasury spending. The system also reduces the impact of strategic voting, as it’s more difficult to manipulate outcomes by backing only the perceived favorite.

However, RCV does have its drawbacks. For instance, the ranking process can be confusing for newcomers or less active participants, particularly when understanding the pros and cons of multiple proposals is required. Too many proposals to rank can overwhelm voters, leading to decision fatigue and reduced participation.

While RCV improves fairness in many ways, it does not entirely prevent large token holders from exerting significant influence in token-weighted systems. Beyond these structural issues, governance attacks remain a risk. Sybil attacks, vote buying, and bribery can undermine the process by incentivizing voters to favor certain rankings. Errors from participants unfamiliar with the ranking mechanics can also result in unintended outcomes.

Despite these limitations, RCV remains a valuable approach for DAOs seeking more expressive, balanced decision-making in complex, multi-option scenarios.

Commit Reveal Voting

Ensuring individual votes are confidential during the decision-making process is essential to protect against bribery, herd behaviour and intimidation. Commit-reveal voting aims to achieve this through a two-prong approach, which aims to enhance privacy, security and fairness through preventing voters from following the majority whilst the vote is underway.

The process unfolds in two distinct stages. Firstly during the commit phase voters submit an encrypted version of their choice through hashing their vote with a secret value, concealing their actual selection. Once the commit period ends, the reveal phase commences, this phase requires voters to disclose both their original vote and the secret used for hashing. This allows the system to verify that the revealed vote matches the earlier commitment.

There are several benefits that make commit-reveal voting an attractive option. Firstly, it prevents participants from adjusting their votes based on others’ choices, protects voter privacy until the process concludes, and minimises the risk of bribery or coercion. Secondly, it helps guard against last-minute whale attacks, where large token holders attempt to sway results just before a vote closes.

However, the system comes with its own trade-offs. It requires two distinct transactions; one for committing and another for revealing, which raises gas costs and adds technical complexity. The longer process can slow decision-making, additionally voter participation may decrease if people forget or fail to reveal their votes, resulting in incomplete outcomes.

Despite these challenges, commit-reveal voting remains a valuable tool for decentralized governance, particularly in environments where confidentiality and resistance to manipulation are essential to preserving fair and secure decision-making.

Liquid Democracy (Delegate Voting)

Liquid Democracy offers a hybrid between direct and representative voting. Participants can vote directly or delegate their vote to someone they trust. Delegation is seen as fluid (liquid) because you take back your voting power at any time, and you can change delegates whenever you want.

For example, in a DAO voting on a protocol upgrade, Alice may choose to vote directly, while Bob, who is less available, delegates his vote to Carol, an expert on the topic. Dave, trusting Bob, delegates his vote to him, but since Bob has already delegated his vote to Carol, Carol ultimately controls the votes of herself, Bob, and Dave. If Dave later changes his mind, he can instantly revoke his delegation and vote himself or delegate to someone else.

Liquid democracy presents several advantages, including more informed decision-making, as members can defer to subject-matter experts, and greater flexibility, which can encourage higher participation by allowing passive members to contribute through delegation. Additionally, delegation chains are fully transparent on-chain, allowing the community to monitor how voting power is distributed.

However, liquid democracy also has its disadvantages. One concern is the potential for centralization, where a small number of popular delegates can accumulate a disproportionate power, catalysing the risk of bribery and collusion. Additionally, members may delegate based on personal relationships or social standing rather than actual expertise. Finally, the added complexity of understanding delegation mechanics can present a barrier for new participants, potentially reducing effective engagement

Holographic Consensus (Prediction Market Boosting)

Holographic consensus aims to solve the voter apathy problem by allowing certain community members to stake tokens to “boost” proposals in which they believe are valuable. Boosted proposals require a lower quorum to pass, enabling DAOs to make decisions even with limited turnout.

It is a clever way to reward attention and prioritisation, especially in busy, large communities. However, just like most governance mechanisms, it has the potential to be abused in a negative manner. Bad actors can flood the system with junk proposals and artificially promote them.

Not a One-Size-Fits-All

As you may be aware by now, it is clear that no single model provides a perfect solution to decentralised governance. Each mechanism represents a different trade-off between security, efficiency, inclusivity and complexity. Some models opt for long-term engagement whereas others focus on speed and equitability. The variety of governance models mirrors the unique needs and dynamics of the communities that use them.

Looking ahead, it is likely that new mechanisms will continue to emerge, including hybrid models, experimental frameworks, and potentially even complete redesigns of how decentralised governance is structured. As DAOs continue to mature and expand, their decision-making frameworks must also evolve to keep pace with the growing complexity and scale. It is paramount that members and contributors remain actively engaged in improving their governance systems, in order to foster a resilient and trustworthy ecosystem which can thrive in the long run.

Ultimately, strong governance is the bedrock on which the future of decentralised systems will depend upon.

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