DAOs (Decentralized Autonomous Organizations) are a relatively new form of governance in which decisions are made by a group of stakeholders, rather than a central authority. However, the current voting process in DAOs can be biased. Some members may be hesitant to express their opinions publicly due to fear of retaliation or pressure from other members. Additionally, the full anonymity of the voting process can lead to a lack of accountability and mistrust among members.
One potential solution to this problem is to design a voting process that is both bias-free and transparent. This can be achieved through the use of zero-knowledge proofs, which allow for the verification of votes without revealing the identity of the voter. Another approach could be the use of multiple rounds of voting or a reputation-based system to mitigate the influence of any one member.
In addition to addressing the issue of bias, it is also important to consider scalability issues in the design and implementation of the voting process. This may involve using off-chain solutions or other scaling techniques to ensure that the voting process can handle a large number of voters.
Overall, this thesis aims to develop a secure and transparent voting system for DAOs, which allows for the participation of all members, and the system should provide transparency after the voting process ends, meaning that the voting outcome can be revealed — including amount of votes, addresses, etc. One potential approach for students to consider is to adapt the GrantShares DAO smart contract implementation as a proof of concept (PoC) for the proposed voting system. With this, a student can explore the different aspects of this problem, from technical considerations to the social/political implications of implementing a bias-free voting process in decentralized systems.
By adapting the GrantShares DAO smart contract implementation, the students can leverage existing code and resources provided by the thesis supervisors to build a proof of concept of their proposed voting system, and they can explore the possibilities of the implementation to eventually bring it to production use.
Supervisors: Dr. Guilherme Sperb Machado, Dr. Bruno Rodrigues, Burkhard Stiller, CSG@IfIback to the main page