Unpacking How Decentralized Autonomous Organizations (DAOs) Work in Practice
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Abstract (arXiv)
Decentralized Autonomous Organizations (DAOs) have emerged as a novel way to coordinate a group of (pseudonymous) entities towards a shared vision (e.g., promoting sustainability), utilizing self-executing smart contracts on blockchains to support decentralized governance and decision-making. In just a few years, over 4,000 DAOs have been launched in various domains, such as investment, education, health, and research. Despite such rapid growth and diversity, it is unclear how these DAOs actually work in practice and to what extent they are effective in achieving their goals. Given this, we aim to unpack how (well) DAOs work in practice. We conducted an in-depth analysis of a diverse set of 10 DAOs of various categories and smart contracts, leveraging on-chain (e.g., voting results) and off-chain data (e.g., community discussions) as well as our interviews with DAO organizers/members. Specifically, we defined metrics to characterize key aspects of DAOs, such as the degrees of decentralization and autonomy. We observed CompoundDAO, AssangeDAO, Bankless, and Krausehouse having poor decentralization in voting, while decentralization has improved over time for one-person-one-vote DAOs (e.g., Proof of Humanity). Moreover, the degree of autonomy varies among DAOs, with some (e.g., Compound and Krausehouse) relying more on third parties than others. Lastly, we offer a set of design implications for future DAO systems based on our findings.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Apr 2023.
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Citing papers per year: 2023: 1; 2024: 1; 2025: 1; 2026: 1.
4 papers.
- 2024Aligning AI with Public Values: Deliberation and Decision-Making for Governing Multimodal LLMs in Political Video Analysiscited by 7
- 2023New Online Communities: Graph Deep Learning on Anonymous Voting Networks to Identify Sybils in Polycentric Governancecited by 1
- 2025Personhood Credentials: Human-Centered Design Recommendation Balancing Security, Usability, and Trustcited by 1
- 2026Paper Agents, Paper Gains: An Empirical Analysis of DeFi Investment Agentscited by 1
- 2026Paper Agents, Paper Gains: An Empirical Analysis of DeFi Investment Agents27 May 2026
- 2025Personhood Credentials: Human-Centered Design Recommendation Balancing Security, Usability, and Trust22 Feb 2025
- 2024Aligning AI with Public Values: Deliberation and Decision-Making for Governing Multimodal LLMs in Political Video Analysis15 Sep 2024
- 2023New Online Communities: Graph Deep Learning on Anonymous Voting Networks to Identify Sybils in Polycentric Governance25 Nov 2023