人工智能将如何改变 DAO：从概念化到增强参与度

人工智能的最新版本（大型语言模型，LLM）已经在改变我们的工作方式。去中心化自治组织 (DAO) 正在改变我们的组织方式。

The latest incarnation of Artificial Intelligence (as Large Language Models, or LLMs) is already changing how we work. Decentralized Autonomous Organizations (DAOs) are changing the way we organize. Now, the two breakthroughs are converging to truly level the field for anyone to actively participate in shaping their own future and that of humanity.

人工智能的最新版本（大型语言模型，LLM）已经在改变我们的工作方式。去中心化自治组织 (DAO) 正在改变我们的组织方式。现在，这两项突破正在融合在一起，真正为任何人积极参与塑造自己和人类的未来奠定了基础。

For context, there are tens of thousands of DAOs. Of those tracked by Deep DAO, the top 2,400 DAOs have a total treasury of over $20B and almost 11 million members; yet less than ⅓ has participated in active governance of the DAO at least once, and less than 1% of DAOs have over 100 members. Since DAOs are meant to democratize power and wealth, such a high degree of centralization of both and the lack of popular participation in DAOs is a critical concern. But LLMs can change that.

就上下文而言，有数以万计的 DAO。在 Deep DAO 追踪的 DAO 中，前 2,400 个 DAO 的总资金超过 20B 美元，拥有近 1100 万会员；然而，只有不到 1/3 的 DAO 至少参与过一次主动治理，不到 1% 的 DAO 拥有超过 100 名成员。由于 DAO 旨在实现权力和财富的民主化，因此两者的高度集中以及 DAO 缺乏民众参与是一个严重的问题。但法学硕士可以改变这一点。

In DeXe Protocol’s recent DAO Talk Panel, they focused on exactly how that may happen (and indeed already is). For this discussion, the host was joined by Deepa, the Founder of ‘grantorb.com,’ a platform that uses AI to unlock millions in grant funding. She was the perfect choice to comprehend the full extent of AI’s impact on DAOs, having worked extensively at the intersection of technology, nonprofits, and fundraising with a focus specifically on both DAOs and AI. Below are some insights from that discussion.

在 DeXe Protocol 最近的 DAO Talk 小组中，他们重点关注了这种情况如何发生（事实上已经发生了）。在这次讨论中，主持人迪帕（Deepa）加入了“grantorb.com”的创始人，“grantorb.com”是一个利用人工智能解锁数百万赠款资金的平台。她是全面理解人工智能对 DAO 影响的最佳人选，她在技术、非营利组织和筹款领域进行了广泛的工作，特别关注 DAO 和人工智能。以下是该讨论的一些见解。

How AI could help conceptualize and onboard for a DAO

人工智能如何帮助 DAO 概念化和上线

Used properly, AI is meant not to replace humans but to do the most menial tasks for them so they can focus on the uniquely human higher-level tasks. Thus, AI can help with explaining your vision for a new DAO to others, from conceptualizing to making the language more accessible for, for example, non-technical or non-artistic audiences. The original idea will still be yours since it takes human originality to come up with something interesting and meaningful enough to attract a following. The AI just saves you time in typing it up, editing it, and breaking into digestible pieces.

如果使用得当，人工智能并不是要取代人类，而是要为他们完成最琐碎的任务，这样他们就可以专注于人类独有的更高级别的任务。因此，人工智能可以帮助向其他人解释您对新 DAO 的愿景，从概念化到使语言更容易被非技术或非艺术受众等理解。最初的想法仍然是你的，因为需要人类的创造力才能想出一些有趣且有意义的东西来吸引追随者。人工智能只是节省了你打字、编辑和分解成易于理解的部分的时间。

Once people join your DAO, you can use AI to create for them customized, individualized onboarding, helping guide all kinds of new members with different experiences, skills, and interests through the onboarding process without a one-size-fits-all approach that makes one spend hours reading documentation and previous discussions, saving a lot of team resources in the process. In DAOs, as with any organization, many people fall off right at the onboarding stage because of the learning curve being too steep, the rules and values not being communicated clearly, and answers not being adequately answered, among other reasons. Personalized AI-powered onboarding can easily solve those issues.

一旦人们加入您的 DAO，您就可以使用人工智能为他们创建定制的、个性化的入职培训，帮助指导具有不同经验、技能和兴趣的各种新成员完成入职流程，而无需采用一刀切的方法，这使得人们花费数小时阅读文档和之前的讨论，在此过程中节省了大量的团队资源。在 DAO 中，与任何组织一样，许多人在入职阶段就掉队了，因为学习曲线太陡、规则和价值观没有清晰传达、答案没有得到充分回答等原因。由人工智能驱动的个性化入职培训可以轻松解决这些问题。

To quote Deepa, “There’s so much to update them on. I think if every DAO had a knowledge graph about everything, it would be very easy with AI. Someone just keeps updating that graph with the different stages of the DAO.”

引用 Deepa 的话说：“有很多东西需要更新。我认为如果每个 DAO 都有一个关于所有事情的知识图，那么使用人工智能就会很容易。有人只是不断更新 DAO 不同阶段的图表。”

Making the DAO multilingual

让 DAO 实现多语言化

Not all of our planet’s 8 billion inhabitants speak English, and even fewer as a first language. AI can enable instant — and quality — translation of all guides and discussions, truly democratizing DAO participation. It can go further by, for example, translating tech, design, marketing, legal, and other concepts into the “language” of the individual user.

我们星球上的 80 亿居民并非全部都会说英语，作为第一语言的就更少了。人工智能可以实现所有指南和讨论的即时且高质量的翻译，真正实现 DAO 参与的民主化。例如，它可以更进一步，将技术、设计、营销、法律和其他概念翻译成个人用户的“语言”。

AI bringing efficiency to DAO management

AI 为 DAO 管理带来效率

Already, AI can help in assigning open tasks in a DAO. Imagine it doing so by matching them with member skills, reputation, and activity. AI can also send members personalized reminders for proposals that match their interests, which would otherwise be drowned in a sea of proposals and general notifications. AI can even help optimize feedback by using each user’s personal interests and criteria for success to judge how well the proposal aligns with the DAO’s mission and with that individual’s values.

人工智能已经可以帮助在 DAO 中分配开放任务。想象一下，它是通过将他们与会员技能、声誉和活动相匹配来实现这一目标的。人工智能还可以向会员发送符合他们兴趣的建议的个性化提醒，否则这些提醒将被淹没在大量建议和一般通知中。人工智能甚至可以通过使用每个用户的个人兴趣和成功标准来判断提案与 DAO 使命和个人价值观的契合程度，从而帮助优化反馈。

AI supercharging engagement

AI 增强参与度

As could be seen from the Deep DAO statistics at the beginning of the article, DAOs suffer from a lack of engagement, which defeats their very purpose. Vastly improving onboarding, summarization, and notification goes far in improving engagement. But what else can AI do in that regard?

从本文开头的 Deep DAO 统计数据可以看出，DAO 缺乏参与度，这违背了它们的初衷。大幅改进入职、总结和通知对于提高参与度有很大帮助。但人工智能在这方面还能做什么呢？

One idea floating around DAO governance nerds is to use gamification. AI can seamlessly gamify engagement by creating enticing and innovative reward systems, task completion points, badges, or other incentives. There is, of course, the risk of excessive gamification drawing in people into it for the gamified gains alone and not for the DAOs mission. So gamification needs to be done responsibly.

DAO 治理迷们的一个想法是使用游戏化。人工智能可以通过创建诱人的创新奖励系统、任务完成点、徽章或其他激励措施来无缝地游戏化参与度。当然，过度游戏化可能会导致人们仅仅为了游戏化的收益而不是为了 DAO 的使命而参与其中。因此游戏化需要负责任地进行。

As Deepa says, “The responsibility for how responsible the AI is lies with the people designing it. If they’re ethical and doing it in good faith, the AI will be responsible.”

正如 Deepa 所说：“人工智能的责任程度取决于设计它的人。如果他们是有道德的并且真诚地行事，人工智能就会承担责任。”

AI can also help create a more meritocratic form of organizing by running elaborate reputation systems. For instance, it can verify member contributions by rapidly verifying on-chain data. Looking at the vast number of data points from each contributor’s actions,

人工智能还可以通过运行复杂的声誉系统来帮助创建一种更加精英化的组织形式。例如，它可以通过快速验证链上数据来验证成员的贡献。查看每个贡献者行为的大量数据点，