Ethereum co-founder Vitalik Buterin proposed a technical overhaul of decentralized autonomous organizations (DAOs), calling for the use of personal AI agents to privately cast votes on behalf of users and help scale digital governance.
The plan, posted on social media platform
Instead, individuals would deploy their own AI model, trained on their past messages and stated values, to vote on the thousands of decisions DAOs face.
“There are thousands of decisions to make, involving many fields of expertise, and most people don’t have the time or skill to be an expert in even one, let alone all of them.” Buterin wrote. “So what can we do? We use personal LLMs to solve the attention problem.”
First is content privacy, ensuring that sensitive data remains confidential. AI agents would operate within secure environments, such as multi-party computing (MPC) or trusted execution environments (TEE), allowing them to process private data without leaking it to the public blockchain.
Secondly is the anonymity of the participant. Buterin called for the use of zero-knowledge proofs (ZKP), a cryptographic tool that allows users to prove they are eligible to vote without revealing their wallet address or how they voted.
This protects against coercion, bribery, and whale watching, where smaller voters imitate the decisions of large token holders.
These AI managers would automate routine participation in governance and flag only key issues for human review.
To filter out low-quality or spam submissions, an emerging problem as generative AI floods open forums, Buterin suggests launching prediction markets. In these, agents could bet on the probability that the proposals would be accepted.
Good bets would generate payouts, incentivizing valuable contributions and penalizing noise.
Buterin also called for privacy-preserving tools, such as multi-party computing and trusted execution environments, that allow AI agents to evaluate sensitive data, such as job applications or legal disputes, without exposing it on a public blockchain.
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