Achieving Unbiased Decision-Making in DAOs: A Privacy-Preserving Approach

Decentralized Autonomous Organizations (DAOs) hold immense promise for collaborative decision-making, but existing governance processes often suffer from biases that hinder their effectiveness. To address this challenge, we are developing Rankify, a platform designed to foster truly meritocratic and transparent decision-making within DAOs.

Our vision is to empower communities to make informed decisions and solve complex problems together, free from the influence of personal biases or social pressures.

Over the past months, we have received significant interest from various sectors, including community managers, team leads, and even the education sector, validating the need for a solution like Rankify.

The Challenge of Unbiased Voting

Ensuring unbiased proposal evaluation and voting in a decentralized environment presents a unique set of challenges. While many researchers suggest Multi-Party Computation (MPC) as a straightforward solution, its practical implementation for real-world scenarios with user-friendly interfaces remains complex.

Rankify’s Four-Stage Protocol

Rankify employs a novel four-stage protocol to achieve unbiased and transparent decision-making:

1. Confidential Proposal Submission: Proposers submit their proposals with the content encrypted, ensuring anonymity while maintaining transparency regarding the submitter’s identity. This prevents bias based on the proposal’s content or the proposer’s reputation.

2. Anonymous Proposal Reveal: After the submission deadline, proposals are decrypted and shuffled, concealing the proposers’ identities. This ensures that voting is based purely on the merit of the proposals themselves, eliminating any halo effect.

3. Private Voting: Participants cast their votes privately. The system prevents voters from voting for their own proposals, ensuring a fair and unbiased voting process.

4. Public Reveal: Once the voting period concludes, all votes and the identities of the proposers are revealed, providing complete transparency and accountability.

Navigating the Complexity

This protocol requires careful consideration of privacy at each stage. While Zero-Knowledge Proofs (ZKPs) combined with MPC may offer a potential solution, their current limitations in terms of user experience make them less suitable for our goals.

MPC, while promising, presents significant development challenges for a small team focused on delivering a seamless user experience. Therefore, we have opted to leverage Trusted Execution Environments (TEEs) using Lit Protocol for our initial implementation, allowing for rapid development and deployment of a decentralized system, there are already useful snippets like decrypting and ability to support social logins looks promising a shortcut for us.

We are also actively experimenting with Ceramic Network for decentralized content proposals, aiming to unlock further privacy-preserving use cases for DAOs. Great that examples with Lit are available

Looking Ahead

We remain committed to exploring alternative solutions and enhancing Rankify’s privacy features. This includes MPC research goal and potential use of FHEnix or Silence Network

Join Us in Shaping the Future of Decentralized Governance

We invite you to join us on this journey towards secure and transparent decentralized decision-making.

• Explore our Public Roadmap: Gain insights into our development plans and progress, join our discord or discussion board.

• Participate in the Rankify Testnet milestone: Follow us on X to be among the first to experience the future of merit-driven communities.

• Support our Development on Gitcoin: GG22 fundraising is live! Contribute to our efforts and help us build a more equitable and collaborative future.

We believe that Rankify can empower communities to make better decisions, fostering a more transparent and accountable ecosystem for decentralized governance.