人工智慧將如何改變 DAO：從概念化到增強參與度

人工智慧的最新版本（大型語言模型，LLM）已經在改變我們的工作方式。去中心化自治組織 (DAO) 正在改變我們的組織方式。

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.

人工智慧的最新版本（大型語言模型，LLM）已經在改變我們的工作方式。去中心化自治組織 (DAO) 正在改變我們的組織方式。現在，這兩項突破正在融合在一起，真正為任何人積極參與塑造自己和人類的未來奠定了基礎。

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，有數以萬計的 DAO。在 Deep DAO 追蹤的 DAO 中，前 2,400 名 DAO 的總資金超過 20B 美元，擁有近 1,100 萬會員；然而，只有不到 1/3 的 DAO 至少參與過一次主動治理，不到 1% 的 DAO 擁有超過 100 名成員。由於 DAO 旨在實現權力和財富的民主化，因此兩者的高度集中以及 DAO 缺乏民眾參與是一個嚴重的問題。但法學碩士可以改變這一點。

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 小組中，他們重點關注了這種情況如何發生（事實上已經發生了）。在這次討論中，主持人迪帕（Deepa）加入了「grantorb.com」的創始人，「grantorb.com」是一個利用人工智慧解鎖數百萬贈款資金的平台。她是全面理解人工智慧對 DAO 影響的最佳人選，她在科技、非營利組織和籌款領域進行了廣泛的工作，特別關注 DAO 和人工智慧。以下是該討論的一些見解。

How AI could help conceptualize and onboard for a DAO

人工智慧如何幫助 DAO 概念化和上線

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.

如果使用得當，人工智慧並不是要取代人類，而是要為他們完成最瑣碎的任務，這樣他們就可以專注於人類獨有的更高層級的任務。因此，人工智慧可以幫助向其他人解釋您對新 DAO 的願景，從概念化到使語言更容易被非技術或非藝術受眾等理解。最初的想法仍然是你的，因為需要人類的創造力才能想出一些有趣且有意義的東西來吸引追隨者。人工智慧只是節省了你打字、編輯和分解成易於理解的部分的時間。

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.

一旦人們加入您的DAO，您就可以使用人工智慧為他們創建客製化的、個人化的入職培訓，幫助指導具有不同經驗、技能和興趣的各種新成員完成入職流程，而無需採用一刀切的方法，這使得人們花費數小時閱讀文件和先前的討論，在此過程中節省了大量的團隊資源。在 DAO 中，與任何組織一樣，許多人在入職階段就落後了，因為學習曲線太陡、規則和價值觀沒有清晰傳達、答案沒有得到充分回答等原因。由人工智慧驅動的個人化入職培訓可以輕鬆解決這些問題。

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 的話說：「有很多東西需要更新。我認為如果每個 DAO 都有一個關於所有事情的知識圖，那麼使用人工智慧就會很容易。有人只是不斷更新 DAO 不同階段的圖表。

Making the DAO multilingual

讓 DAO 實現多語言化

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.

我們星球上的 80 億居民並非全部都會說英語，作為第一語言的就更少了。人工智慧可以實現所有指南和討論的即時且高品質的翻譯，真正實現 DAO 參與的民主化。例如，它可以更進一步，將技術、設計、行銷、法律和其他概念翻譯成個人用戶的「語言」。

AI bringing efficiency to DAO management

AI 為 DAO 管理帶來效率

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.

人工智慧已經可以幫助在 DAO 中分配開放任務。想像一下，它是透過將他們與會員技能、聲譽和活動相匹配來實現這一目標的。人工智慧還可以向會員發送符合他們興趣的建議的個人化提醒，否則這些提醒將被淹沒在大量建議和一般通知中。人工智慧甚至可以透過使用每個使用者的個人興趣和成功標準來判斷提案與 DAO 使命和個人價值觀的契合程度，從而幫助優化回饋。

AI supercharging engagement

AI 增強參與度

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?

從本文開頭的 Deep DAO 統計數據可以看出，DAO 缺乏參與度，這違背了它們的初衷。大幅改進入職、總結和通知對於提高參與度有很大幫助。但人工智慧在這方面還能做些什麼呢？

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 治理迷們的一個想法是使用遊戲化。人工智慧可以透過創造誘人的創新獎勵系統、任務完成點、徽章或其他激勵措施來無縫地遊戲化參與度。當然，過度遊戲化可能會導致人們僅僅為了遊戲化的收益而不是為了 DAO 的使命而參與其中。因此遊戲化需要負責任地進行。

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 所說：「人工智慧的責任程度取決於設計它的人。如果他們是有道德的並且真誠地行事，人工智慧就會承擔責任。

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,

人工智慧還可以透過運行複雜的聲譽系統來幫助創建一種更精英化的組織形式。例如，它可以透過快速驗證鏈上資料來驗證成員的貢獻。查看每個貢獻者行為的大量數據點，