A technical overhaul of decentralized autonomous organizations (DAOs) was proposed by Ethereum cofounder Vitalik Buterin, who called for the use of personal artificial intelligence agents to privately cast votes on behalf of users and help scale digital governance.
It is a plan, which was published on social media site X one month after Buterin criticised DAOs for drifting into low participation and power centralization, to divert users away from delegating votes to large token holders.
Rather, people would use their own AI model (based on the messages and stated values) to vote on thousands of decisions DAOs make.
It is a phrase that has many thousands of decisions to make, with the domains of expertise; most people don’t have time or skill to be experts in even one, let alone all of them. In a poem by ” Buterin, he wrote. What do we do? We use personal LLMs to solve the attention problem. Paraphrast.
The first is privacy of content, so that sensitive information can be kept secret. Similarly, AI agents would operate in safe environments like multi-party computation (MPC) or trusted execution environments (TEEs), so they can process private data without leaking it to the public blockchain.
Second is the anonymity of the contestant. In a bid to promote zero-knowledge proofs (ZKPs), Buterin called for the use of cryptographic tool that allows users to prove they can vote without revealing their wallet address or how they voted.
This guards against coercion, bribery, and whale watching, where smaller voters mimic the decisions of large token holders.
These AI stewards would automate routine governance participation and flag only key issues for human review.
And Buterin says launching prediction markets is an emerging problem as generative AI floods open forums to filter out low-quality or spammy proposals, which she suggests in order to avoid the use of “fake” algorithms. Agents in these may bet on the possibility that proposals would be accepted in a bid, such as .
Good bets would earn payouts, incentivizing valuable contributions while penalizing noise.
Yeterin, for instance, called for privacy-preserving tools like multi-party computation and trusted execution environments that allow AI agents to evaluate a person’s data (such as job applications or legal disputes), without showing it on e-battering public blockchain.
Read more: From 2016 hack to $150M Endowment: the DAO’s second act focuses on Ethereum security
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