Pairwise: Simplifying Choices, Amplifying Voices
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Open-source, off-chain voting dApp streamlines community decisions with a simple binary choice system, using an Elo rating system-like algorithm for objective outcomes and various practical use cases, including retroactive funding, decentralized curation, user research, and future developments like incentivizing participation, semi-anonymous voting, and filtering unwanted projects.

Pairwise was designed to make voting simple and fun. Pairwise is an open-source, off-chain voting dapp (like Snapshot) that streamlines community signaling by letting users select between just two options and then aggregating their choices into a quantifiable result.

Pairwise is designed to be user-friendly and intuitive, allowing users to make many simple choices and then the algorithm behind the scenes pumps out a final ranking for them to adjust or approve. The algorithm is very similar to the Elo rating system which is the dominant way of doing this work in the default world (chess, video games, professional and college sports, etc.) Pairwise converts these simple subjective inputs into objective, measurable outputs, minimizing the cost and cognitive burden of voting.]

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Practical Use Cases

1. Retroactive funding: Pairwise, combined with categories, is what we are having more fun with to potentiate RetroPGF. Categories help make Pairwise voting easier and faster. By grouping similar projects, voters get to compare apples to apples and can get accurate rankings with fewer clicks. This approach also enables three benefits that would otherwise not be possible.

  • Enabling Expertise to Shine: Our approach allows voters to focus on their areas of expertise and interest. With this categorization, voters will rank projects in the domains where their expertise and interests lie, ensuring that the ranking of projects is informed by knowledgeable insights, without imposing on voters the need to review all the projects to participate. This approach allows us to maximize the value derived from voters' time and contributions, and for a more effective ranking of projects, as each voter brings their specialized knowledge to the table, aiding in Project Discovery to Build Ecosystem Network Effects.

  • Making DAOing Fun: Voting in a DAO shouldn’t have to feel like work. It should be fun and rewarding! DAOs to get excited about every round of Retro round!. It will feel like a tournament-esque competition where participants discover their own preferences and a lot of cool projects. Voters will talk about their opinions on Twitter and in real life (IRL) while anticipating the voting results. The voting process is simple and fun; it can be done in one solid hack session or, since your voting progress will be saved, it can be done in many parts during boring calls and while you have free moments throughout the week. The voting experience will feel less like voting and more like scrolling on social media or swiping on a dating app. Let’s be real, it won’t be that amazing, but still much better than the normal voting process ;-)

2. Decentralized Curation and Ranking: Pairwise can be used to compare, rank and curate projects, content, products, or services, and can serve as a “decentralized suggestion algorithm”. One use case being explored is with Giveth, where users can vote on projects that they are passionate about, which would then feed into the website ranking. This not only allows the community to vote on what projects are important for them, but it also opens the door for new projects to surface that otherwise would have not received the same exposure.

3. User research: A fun use case is user research, where the community can be polled on what their subjective preferences are. For example, this can be used within any DAO to decide on features as kind of a “hot or not” game, where users can vote on specific designs or traits, to determine which ones are most valued by the community.

Future Development

  • Reward Participation: Financial compensation for votersis crucial for acknowledging efforts. We plan to allocate a portion of the RetroPGF budget for voter compensation, with rewards scaling based on the number of categories reviewed, capped once 33% of the categories are ranked. This system encourages voters to concentrate on their areas of expertise, ensuring meaningful participation. To combat gaming of the system, we will employ traditional analytics tools to monitor application usage, distinguishing between genuine engagement and opportunistic behavior aimed at farming rewards. Only authentic efforts to review and judge projects will be rewarded, ensuring fairness in the distribution process. The Pairwise voting mechanism, distinct from snapshot methods, facilitates this by making it easier to track user interactions and maintain transparency in reward calculations, with all processes and outcomes being publicly available.

  • Semi-Anonymous Voting: Addressing the dilemma between the desire for anonymity and the influence of social pressure in voting, we introduce the concept of semi-anonymous voting. This approach allows for a selected group of individuals to be aware of voters' identities, striking a balance between preventing biased voting for acquaintances and eliminating undue social pressure. Semi-anonymous voting aims to preserve the integrity of the voting process by ensuring that votes are cast based on merit rather than personal relationships, while still offering a degree of privacy to participants. This middle ground is crucial for fostering a fair and pressure-free voting environment.

  • Tinder Filtering: One of the feedback points we received during the Optimism RetroPGF round was that many projects a badgeholder didn't want to support kept reappearing. We believe that a Tinder-style filtering process could be both fun and useful for removing the projects the voter doesn't want to see again.

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