Ranked-Choice Voting

The most common RCV method is the instant-runoff voting (IRV) algorithm. Voters rank candidates (e.g., proposals, delegates). The candidate with the fewest first-choice votes is eliminated, and their votes are redistributed to the next preferred candidate on each ballot. This process repeats until one candidate achieves a majority, ensuring the winner has broad support.

• Eliminates vote-splitting: Prevents a less-preferred candidate from winning due to a split majority.
• On-chain execution: The tallying logic is encoded in a smart contract for transparency and automation.

Unlike simple yes/no or single-choice voting, RCV allows voters to express a spectrum of preferences. This is critical for DAOs where multiple competing proposals may have merit. A voter can signal:

• Primary support for their favored option.
• Secondary support for a compromise, preventing a "lesser of two evils" dilemma.
• Clear opposition by ranking disliked options last.

This leads to outcomes that better reflect the collective will and can reduce polarization.

The Optimism Collective uses RCV (via Snapshot) to allocate millions in grant funding through its Retroactive Public Goods Funding (RPGF) rounds. Project applicants are ranked by badgeholders. This system:

• Surfaces consensus among many high-quality projects.
• Mitigates tactical voting where voters might otherwise only support a single favorite.
• Demonstrates how RCV manages complex allocation decisions with a large, diverse electorate.

While powerful, RCV introduces complexity:

• Voter Education: The process is less intuitive than simple voting, potentially lowering participation.
• Gas Costs: On-chain tallying of complex ballots can be expensive, favoring off-chain signaling with on-chain execution.
• Attack Vectors: Designs must consider collusion (e.g., block voting) and strategic ranking (not ranking a strong opponent).
• Winner Selection: Different RCV algorithms (e.g., Condorcet method) can produce different winners from the same ballots.

Quadratic Voting (QV) is another advanced mechanism often compared to RCV. In QV, voters allocate a budget of "voice credits" to proposals, where the cost to vote is quadratic relative to the vote strength. This aims to measure the intensity of preference rather than just the order.

• RCV vs. QV: RCV finds a broadly acceptable winner; QV optimizes for aggregate welfare by allowing voters to signal how strongly they care.
• Combined Use: Some systems explore hybrid models, using RCV to shortlist and QV to finalize funding amounts.

RCV requires voters to understand a more complex ranking process, which can lead to ballot exhaustion where a voter's choices are eliminated before a winner is decided. Key challenges include:

• Voter education is critical to prevent unintentional spoiler effects.
• UI/UX design must clearly guide users through ranking multiple candidates.
• Spoiled ballots can occur if rankings are incomplete or invalid, potentially disenfranchising voters.

The instant-runoff tabulation process is more computationally intensive than simple plurality voting. On-chain, this translates to:

• Higher gas costs for both casting ranked ballots and executing the tallying logic.
• Increased block space consumption, especially for elections with many candidates.
• A trade-off between on-chain verifiability and the cost of executing complex tallying smart contracts.

Fully transparent on-chain voting can undermine RCV's integrity by enabling vote buying or coercion. Adversaries could demand proof of a specific ranking. Mitigations include:

• Commit-reveal schemes or zero-knowledge proofs (ZKPs) to hide rankings until the vote closes.
• Minimal viable anonymity designs that separate voter identity from ballot content, though this adds significant protocol complexity.

RCV's fairness depends on one-person-one-vote. Blockchain's pseudonymous nature requires robust Sybil resistance to prevent an entity from controlling multiple voting identities (wallets). Solutions often involve:

• Proof-of-personhood or soulbound token (SBT) systems to anchor identity.
• Delegation to oracles or trusted registries for identity verification, which introduces centralization trade-offs.

A core promise of on-chain voting is cryptographic verifiability. For RCV, this means every participant must be able to audit:

• That their ballot was recorded correctly (individual verifiability).
• That the tabulation algorithm was executed faithfully without error or manipulation (universal verifiability).
• This requires publishing all ballots and the full elimination sequence, which conflicts with privacy goals.

Lack of standards for RCV smart contracts and data formats hinders ecosystem development. Challenges include:

• No common interface for wallets and dApps to interact with different RCV implementations.
• Fragmented tallying logic, making it difficult to audit or compare results across platforms.
• Interoperability issues for cross-chain governance, where votes may need to be aggregated from multiple ledgers.

Instant-Runoff Voting is the most common single-winner form of Ranked-Choice Voting. It works by eliminating the candidate with the fewest first-choice votes and redistributing their ballots to the next-ranked candidate still in the race. This process repeats until one candidate achieves a majority (>50%) of the active votes. It is used in jurisdictions like New York City and the state of Maine for mayoral and congressional elections.

Single Transferable Vote is the multi-winner proportional representation version of RCV. Voters rank candidates in multi-seat districts. A quota (e.g., the Droop quota) is calculated to determine the votes needed to win a seat. Surplus votes from elected candidates and votes from eliminated candidates are transferred to remaining candidates based on voter preferences, ensuring more proportional outcomes. It is used in Ireland, Australia (Senate), and Cambridge, Massachusetts.

A Condorcet method is a type of ranked voting system that aims to elect the Condorcet winner—a candidate who would beat every other candidate in a head-to-head matchup. These systems evaluate the full matrix of pairwise comparisons between candidates. While RCV (IRV) does not guarantee the election of a Condorcet winner, some ranked systems, like Ranked Pairs or the Schulze method, are explicitly designed to do so.

An exhausted ballot occurs in RCV when a voter's ballot can no longer be counted in the final round because all candidates ranked on that ballot have been eliminated. This can happen if a voter does not rank all candidates or only ranks candidates who are eliminated early. The percentage of exhausted ballots is a key metric for evaluating the effectiveness and voter comprehension of an RCV election.

Plurality Voting, or First-Past-The-Post (FPTP), is the conventional system RCV is often compared to. In FPTP, voters select only one candidate, and the candidate with the most votes wins, even without a majority. This system is criticized for vote splitting and the spoiler effect, where similar candidates split the vote, allowing a less-preferred candidate to win. RCV is designed to mitigate these issues by capturing voter preferences more fully.

The Borda Count is a ranked voting system where points are assigned based on a voter's ranking (e.g., 3 points for 1st, 2 for 2nd, 1 for 3rd). The candidate with the highest total points wins. Unlike RCV/IRV, it is a positional voting system that aggregates scores rather than simulating sequential elimination rounds. It is more susceptible to strategic voting through burying (ranking a strong opponent last) and is used in contexts like sports awards.