The nearby foundation is the development of artificial intelligence enabled by “delegates” who eventually voted on behalf of decentralized autonomous organizations (DAO) members, aimed at addressing the voter’s low participation that has become commonplace with many protocols.
Lane Rettig, a researcher on the nearby foundation, who specializes in AI and Management, told Cointelegraph that the development of AI-powered management management is still in development. The nearby foundation administers the layer-1 near the protocol.
The idea is to delegate a user, or “digital twin,” will learn their preferences and then act accordingly when it comes to time to make management decisions. This will change the process of voting with a “math problem” that can “happen immediately.”
“Then you want to set this thing loose, and it’s kind of gestures on your behalf and votes for you. It cares for you. When you know, the proposals are relevant to you,” he said in an interview with the token2049 conference in Singapore.
“That is in a sense, almost our vision at the end of the game for it, where we are replacing all human actors with a digital twin, if you want to call it, to solve this voter’s apathy, participation issue.”
It is Attached The average rate of participation in DAOS is between 15% and 25%, which can lead to issues such as centralization of power, ineffective decision -making, and, in the worst cases of situations, managementWhere a bad actor gets enough tokens to pass a destructive proposal without other members noticed.
Human input is still part of the process
Rettig said it is likely that there will still be a human element involved in the process.
He said he was a “solid believer that should always have a person in the loop,” because there are categories of measures that are too critical to leave only an AI, such as those about funding allocations or strategy strategies.
“I think it’s definitely a category of things where you want the person to make the final decision, pull the trigger,” he said.
“And said that, not only can it leave you, it can also be said, based on what I know about you, I think you should vote this way, but you should vote right, and they can know, if it makes a mistake, it means that there is something wrong with the context.”
AI agents are already widespread throughout the crypto and are used to develop web3 applications, launch tokens, and interact with services and autonomy protocols, with several platforms Exploring the use of AI agents For trading to automatically tasks and make real-time decisions.
Delegates trained in user behavior
Similar to how Generative AI chatbots Trained, like Openai’s chatgpt, Rettig said the AI delegates would learn through contacts with users, including a process of interviewing, voting history and messages on social platforms such as Telegram and Discord.
“When you are kind of switching this agent, you just get to know it, right? It’s kind of need to know your political preferences, the kind of projects you care about, and where you think it should be allocated,” he added.
Investment manager Vaneck estimates that the Number of AI agents In the crypto industry exceeds 10,000 by the end of 2024 and is expected top 1 million in 2025. However, there are concerns that AI agents place the same security risks And important decisions can decompose if it is fully relied on.
One of the ways a nearby foundation tries to ensure that delegates remain aligned with a user’s values is through a proven model training model, which shows proof cryptographic of training cycles and inputs, according to Rettig.
AI delegate rollout is a stable process
It’s close primary Dao, the nearby digital collective, has already implemented an AI tool called Pulse, which tracks community sentiment, summarizes discord forums and featuring important content, Rettig said.
Related: AI agents need crypto to work in financial markets: Coinbase Exec
In its delegates, he said they start with “low -hanging fruit,” and its first models are very similar to chatbots, with “small agencies,” which advise proposals and provide useful information, contexts and can fill the basic templates for users so they can feel better.
The final controlling will take place in stages, with the AI delegates first representing large groups with similar voting preferences, then moved toward the presence of an individual delegate for each person, and perhaps even the AI delegates CEOs.
“Then the management becomes a math problem, you just summarize it. Every time a vote comes, it can happen almost immediately because you have all the agents there, and they know how everyone will vote early, then boom, you’re done.”
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