國會關注去中心化人工智慧的理由

營運去中心化雲端 Akash 網路的 Overclock Labs 財務長 Cheng Wang 表示，立法者在開始監管人工智慧時，不能忽視去中心化人工智慧。

Lawmakers must recognize the unique needs of decentralized AI, a critical yet often overlooked sector at the intersection of blockchain and artificial intelligence, as they begin to regulate AI. Despite this crossover, decentralized AI cannot be legislated through a financial lens, nor can it be forced into AI regulations. Given its overlap in distinct sectors, however, there’s a real chance lawmakers will try to fold it into AI and crypto bills – or overlook it altogether – which would be a missed opportunity for innovation in this country.

立法者在開始監管人工智慧時，必須認識到去中心化人工智慧的獨特需求，這是區塊鏈和人工智慧交叉領域的關鍵但經常被忽視的領域。儘管存在這種交叉，但去中心化人工智慧不能透過金融視角進行立法，也不能強行納入人工智慧法規。然而，考慮到它在不同領域的重疊，立法者很有可能試圖將其納入人工智慧和加密貨幣法案中——或完全忽略它——這將錯失這個國家的創新機會。

Powerful framework

強大的框架

Decentralized AI allows for the distribution of data, computation, and decision-making processes across multiple devices or nodes, enabling them to work together without relying on a centralized authority, often utilizing open source software and models. This gives developers the tools to share their data collaboratively to build AI models, and to access compute from a diverse range of sources. It’s a powerful framework that empowers these developers to contribute to the AI ecosystem without the need to manage the entire process themselves, enabling researchers and startups to participate in a field where rising costs and difficulty of access threaten to push them out.

去中心化人工智慧允許跨多個設備或節點分佈資料、計算和決策過程，使它們能夠在不依賴中心化權威的情況下協同工作，通常利用開源軟體和模型。這為開發人員提供了協作共享資料以建立人工智慧模型以及從各種來源存取計算的工具。它是一個強大的框架，使這些開發人員能夠為人工智慧生態系統做出貢獻，而無需自己管理整個流程，從而使研究人員和新創公司能夠參與成本上升和訪問難度增加可能將他們擠出的領域。

That’s why it’s imperative lawmakers not overlook decentralized AI as they begin to regulate AI. It’s probably human nature to ignore, considering the broader AI industry is exploding and dominated by some of the world’s biggest corporations. They’re acquiring startups, pushing advancements, and launching new products at a breakneck pace. While there’s nothing wrong with Microsoft, Meta, Alphabet, and others investing heavily in the industry, lawmakers need to create space for researchers, entrepreneurs, and developers to thrive as well; that entails among other things remaining vigilant on antitrust, and ensuring that government-backed R&D funds don’t benefit the giants alone.

這就是為什麼立法者在開始監管人工智慧時不能忽視去中心化人工智慧。考慮到更廣泛的人工智慧產業正在爆炸性成長並由一些世界上最大的公司主導，忽視這一點可能是人性。他們正在以極快的速度收購新創公司、推動進步並推出新產品。雖然微軟、Meta、Alphabet 和其他公司在該行業的大力投資並沒有什麼問題，但立法者需要為研究人員、企業家和開發人員的蓬勃發展創造空間；除此之外，這需要對反壟斷保持警惕，並確保政府支持的研發資金不會只讓巨頭受益。

And while Congress is making welcome progress to advance comprehensive legislation that would clarify the rules of the road for crypto, the bills are one-dimensional – financial in nature – and don’t address the obvious difference between an underlying digital asset of a protocol versus the decentralized AI applications running on the same protocol. Financial regulators shouldn’t end up overseeing decentralized AI just because projects issue tokens; that would be like the SEC regulating toothpaste because Johnson & Johnson issues common stock.

儘管國會在推進全面立法以澄清加密貨幣發展規則方面取得了可喜的進展，但這些法案是一維的——本質上是金融的——並且沒有解決協議的基礎數字資產與加密貨幣之間的明顯區別。金融監管機構不應該僅僅因為項目發行代幣就最終監管去中心化人工智慧；這就像美國證券交易委員會監管牙膏一樣，因為強生公司發行普通股。

The next wave

下一波

It’s important we get this right, because decentralized AI is a critical field that can salvage the organizations that gave birth to the AI revolution – and possibly bring us the next wave. The universities that created the concept of machine learning and neural networks are under threat, as they cannot compete with Big Tech as it snaps up the world’s GPUs and top talent. In a similar vein, the kinds of startups that brought AI to market are facing similar constraints and oftentimes must defer projects. Without those engines of U.S. innovation working properly, progress will rest in the hands of a few large corporations. It’s a lesson that lawmakers will want to heed, as these universities and small businesses help form the fabric of the American economy, and create jobs and opportunities for constituents.

我們正確對待這一點很重要，因為去中心化人工智慧是一個關鍵領域，可以挽救催生人工智慧革命的組織，並可能為我們帶來下一波浪潮。創造機器學習和神經網路概念的大學正面臨威脅，因為它們無法與搶佔世界 GPU 和頂尖人才的大型科技公司競爭。同樣，將人工智慧推向市場的新創公司也面臨類似的限制，並且常常必須推遲專案。如果美國創新引擎無法正常運轉，進步將掌握在少數大公司手中。這是立法者需要注意的一個教訓，因為這些大學和小企業有助於形成美國經濟的結構，並為選民創造就業機會和機會。

Decentralized AI can counter this trend of market concentration. The field allows organizations with limited funds to share data and compute across nodes, with developers stitching together a network of multiple databases to feed their models and dispersed GPUs to power them. It’s a more affordable solution that allows smaller players to participate and contribute. It also addresses many of the concerns about data privacy: developers can process data locally, which minimizes the need to transfer sensitive information to centralized servers. This reduces the risk of data breaches and unauthorized access.

去中心化的人工智慧可以對抗這種市場集中化的趨勢。該領域允許資金有限的組織跨節點共享資料和運算，開發人員將多個資料庫的網路拼接在一起以提供模型和分散的 GPU 來為其提供動力。這是一種更實惠的解決方案，允許較小的參與者參與並做出貢獻。它還解決了許多有關數據隱私的問題：開發人員可以在本地處理數據，從而最大限度地減少將敏感資訊傳輸到集中式伺服器的需要。這降低了資料外洩和未經授權存取的風險。

Congress's turn

輪到國會了

All this goes to show the importance of establishing rules and regulations that allow decentralized AI to flourish. Congress must establish clear regulations for data privacy and security to protect individuals’ information when processed locally, and promote transparency and accountability in AI algorithms that can protect ethical standards and prevent bias in decentralized systems.

所有這些都表明建立允許去中心化人工智慧蓬勃發展的規則和法規的重要性。國會必須制定明確的資料隱私和安全法規，以保護本地處理的個人訊息，並促進人工智慧演算法的透明度和問責制，以保護道德標準並防止去中心化系統中的偏見。

Lawmakers should consider a unique regulatory framework for decentralized AI, separate from traditional AI regulations in the Algorithmic Accountability Act and from financial guidelines covered in the Blockchain Regulatory Certainty Act. The new legislation would need to address the particular challenges of decentralized AI, ensuring transparency in algorithmic decisions, and providing guidelines on accountability in decentralized networks. Further, Congress should look at expanding funding opportunities under the National AI Initiative Act to ensure decentralized AI projects – especially those from universities and small businesses – receive government R&D funds and tax incentives, preventing Big Tech from monopolizing AI innovation. Along those lines, Congress would be wise to consider bolstering antitrust enforcement to stop major corporations from controlling critical AI infrastructure.

立法者應考慮為去中心化人工智慧制定獨特的監管框架，與《演算法責任法案》中的傳統人工智慧法規以及《區塊鏈監管確定性法案》中涵蓋的財務準則分開。新立法需要解決去中心化人工智慧的特殊挑戰，確保演算法決策的透明度，並提供去中心化網路問責制的指導方針。此外，國會應考慮擴大《國家人工智慧倡議法案》下的資助機會，以確保去中心化的人工智慧計畫——尤其是來自大學和小型企業的計畫——獲得政府研發資金和稅收優惠，防止大型科技公司壟斷人工智慧創新。沿著這些思路，國會應該明智地考慮加強反壟斷執法，以阻止大公司控制關鍵的人工智慧基礎設施。

And the responsibility doesn’t rest solely on Congress’ shoulders. With lawmakers paying renewed attention to crypto and AI, now is the time for proponents of decentralized AI to speak up and advocate for the industry. And let’s face it, the industry hasn’t always done a stellar job of communicating what it does and what it needs to thrive. Yes, the technology is complex, but that doesn’t mean advocates can’t go beyond the technical language and articulate it in a way staffers and legislators without engineering degrees can understand

而且責任不僅落在國會的肩膀上。隨著立法者重新關注加密貨幣和人工智慧，現在是去中心化人工智慧的支持者為該行業發聲和倡導的時候了。讓我們面對現實吧，該行業在傳達其所做的事情以及蓬勃發展所需的內容方面並不總是做得很好。是的，這項技術很複雜，但這並不意味著倡議者不能超越技術語言，並以沒有工程學位的工作人員和立法者可以理解的方式闡明它