Vitalik discussed the role of AI in governance in this tweet. Roughly speaking, it is terrifying to let AI act as the "government" directly: when AI is weak, it will make a bunch of garbage decisions; When AI is strong, it may directly destroy humanity. But if used well, AI can enhance democracy and decentralized governance (such as DAO on Ethereum, similar to community self-governing organizations), making everyone more engaged. Then, he pointed out the difficulty of decentralized governance: decentralized governance is difficult to implement because there are too many decisions and they are too professional, and most people do not have the time or ability to fully understand. The usual solution is "delegation" - selecting a few people to help you make decisions, but this will concentrate power in the hands of a few people, and others clicking the "delegation" button will lose their influence. Then, his solution is to use personal AI (LLM) to solve the problem of "attention deficit". Including the following aspects: 1. Personal governance agency AI infers your preferences based on your articles, chat records, direct statements, etc., and automatically votes for you. If AI is unsure about an important issue, it will directly ask you and provide background information. 2. Public dialogue proxy Good decision-making is not simply about averaging everyone's opinions. It requires first summarizing information and then having each person (or their AI) respond based on the summary. This includes: AI summarizing your viewpoint (without compromising privacy) and identifying common ground among everyone's viewpoints. 3. Suggested market Use market forecasting to screen high-quality inputs (proposals or arguments). Anyone who submits an idea, AI can place a bet, and if the mechanism accepts this input, the person placing the bet can make money. This encourages high-quality contributions. 4. Decentralized governance with privacy The weakness of decentralized governance is the inability to handle confidential information, such as adversarial negotiations, internal disputes, and fund allocation. Usually, it relies on a few people having great power. But using multi-party computation (MPC, technically TEE or circuit encryption) can allow many people (through their AI) to input opinions without revealing secrets: your AI looks at private information and outputs judgments, but neither you nor others can see the details. 5. The Importance of Privacy These methods use more personal information, so privacy is extremely important. Two types: participant anonymity (using ZK zero knowledge proof), content privacy (AI does not leak randomly, using MPC calculation). In short, he wants to use AI as a tool to enhance human governance, rather than replacing humans and avoiding power concentration. Vitalik's ideas have always been forward thinking and great, which may represent the direction of DAO governance in the future. However, there are also some issues worth exploring regarding his solution alone: 1. AI bias and manipulation risks Personal AI infers preferences based on your history, but if your data is contaminated (such as fake news affecting your chat history), AI may make incorrect decisions. Even worse, hackers or bad actors can manipulate AI models, leading to collective decision-making biases. Vitalik mentioned privacy, but did not elaborate on how to prevent the AI itself from being tampered with. 2. The ambiguity of uncertainty and importance judgment When AI decides on 'important' issues, it asks you, but who defines' important '? The judgment criteria of AI may not be accurate, resulting in key issues not being asked to you or trivial matters bothering you. In practice, AI is weak in understanding complex contexts and is prone to errors. 3. Privacy leakage when summarizing information When summarizing the opinions of public dialogue agents, they say 'do not expose private information', but there is always a risk of leakage when AI processes data from multiple people. Even with MPC, the technology is not perfect (TEE has hardware vulnerabilities, and clogged circuits are only suitable for small-scale use). If the AI model itself has backdoors, privacy is lost. 4. Predicting the Gamification of the Market The market is indeed cool, but predicting the market is often manipulated by big players (such as drowning out small players with money). Is there a problem with AI betting: If AI is optimized as a "winning machine", it may prioritize making money over high-quality input, leading to a proliferation of junk proposals. 5. Accessibility and inequality These systems assume that everyone has powerful AI and computing resources, but what about the poor or tech novices? DAO has become biased towards the wealthy and idle, and using AI may exacerbate inequality - the rich use better AI, while the poor have weaker AI and more biased decision-making. Vitalik proposes' empowerment ', but how to address the issue of digital divide? 6. The overall risk of excessive reliance on AI Even if AI is a tool, once it becomes popular, people may be too lazy to think for themselves, indirectly making AI "a government". If AI makes mistakes (such as hallucinations), large-scale governance will collapse. Vitalik opposes the idea of "AI becoming a government", but his plan still gives too much power to AI. When AI is weak, it becomes "garbage", and when AI is strong, it remains a "doom" hazard. The above issues are not about Vitalik's ideas being wrong, but rather about potential problems that may arise during the implementation process.