AI assistants can change management: Buterin
Vitalik Buterin, founder of Ethereum, says that artificial intelligence will help create more efficient decentralized governance models and allow users to make better informed decisions.
Buterin said in a Sunday X post that one of the main issues with democratic and decentralized governance styles like DAOs is “limitations on human attention spans,” because many decisions require too many skills or time, and most don't have them.
“The usual solution, delegation, is disempowerment, it leads to a small group of delegates who control decision-making, whose supporters have no influence after pressing the button of delegation,” he said.
The average participation rate in The DAO is estimated to be between 15% and 25%. This can lead to issues such as centralization of power and ineffective decision making. Worst cases can lead to administrative attacks, when a bad actor gets enough signals to pass a harmful idea without other members noticing.
AI-powered assistants that vote for you
Buterin proposed that personal assistant large-scale linguistic models (LLMs) could help solve the “attention problem” by giving the user voice the relevant information they need.
“If the management method depends on you to make many decisions, a personal representative can give you all the necessary votes based on the choices you make in your personal text, conversation history, direct statements,” he said.
“If the representative is not sure how to vote on an issue and believes that the issue is important, he should ask you directly and give you all the relevant context,” Buterin added.
Len Rettig, a Near Foundation researcher specializing in AI and governance, told Cointelegraph last year that the nonprofit was working on a similar idea: AI-powered digital twins that would vote on behalf of DAO members to address low voter turnout.
An important aspect to protect privacy
Another challenge in highly decentralized governance arises when key decisions depend on private or confidential information, such as negotiations, internal disputes or funding choices, Buterin said.
Related: Vitalik Buterin floats fake transactions to improve crypto security
“Typically, organizations solve this by appointing individuals with significant authority to perform those tasks,” he said.
An alternative solution could be for users to put their personal LMM in a black box, where the LMM looks at the personal information, makes a judgment based on that, and just makes the judgment. You will not see the personal information, and no one will see your private LLM contents.
“All of these approaches involve each participant using a lot of information about themselves and providing very large amounts of resources, so protecting privacy becomes even more important,” Buterin said.
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