国会关注去中心化人工智能的理由

运营去中心化云 Akash 网络的 Overclock Labs 首席财务官 Cheng Wang 表示，立法者在开始监管人工智能时，不能忽视去中心化人工智能。

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.

立法者在开始监管人工智能时，必须认识到去中心化人工智能的独特需求，这是区块链和人工智能交叉领域的一个关键但经常被忽视的领域。尽管存在这种交叉，但去中心化人工智能不能通过金融视角进行立法，也不能强行纳入人工智能法规。然而，考虑到它在不同领域的重叠，立法者很有可能试图将其纳入人工智能和加密货币法案中——或者完全忽略它——这将错失这个国家的创新机会。

Powerful framework

强大的框架

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.

去中心化人工智能允许跨多个设备或节点分布数据、计算和决策过程，使它们能够在不依赖中心化权威的情况下协同工作，通常利用开源软件和模型。这为开发人员提供了协作共享数据以构建人工智能模型以及从各种来源访问计算的工具。它是一个强大的框架，使这些开发人员能够为人工智能生态系统做出贡献，而无需自己管理整个流程，从而使研究人员和初创公司能够参与到成本上升和访问难度增加可能将他们挤出的领域。

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.

这就是为什么立法者在开始监管人工智能时不能忽视去中心化人工智能。考虑到更广泛的人工智能行业正在呈爆炸式增长并由一些世界上最大的公司主导，忽视这一点可能是人性。他们正在以极快的速度收购初创公司、推动进步并推出新产品。虽然微软、Meta、Alphabet 和其他公司在该行业的大力投资并没有什么问题，但立法者需要为研究人员、企业家和开发人员的蓬勃发展创造空间；除其他外，这需要对反垄断保持警惕，并确保政府支持的研发资金不会只让巨头受益。

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.

尽管国会在推进全面立法以澄清加密货币发展规则方面取得了可喜的进展，但这些法案是一维的——本质上是金融的——并且没有解决协议的基础数字资产与加密货币之间的明显区别。在同一协议上运行的去中心化人工智能应用程序。金融监管机构不应该仅仅因为项目发行代币就最终监管去中心化人工智能；这就像美国证券交易委员会监管牙膏一样，因为强生公司发行普通股。

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.

我们正确对待这一点很重要，因为去中心化人工智能是一个关键领域，可以挽救催生人工智能革命的组织，并可能为我们带来下一波浪潮。创建机器学习和神经网络概念的大学正面临威胁，因为它们无法与抢占世界 GPU 和顶尖人才的大型科技公司竞争。同样，将人工智能推向市场的初创公司也面临着类似的限制，并且常常必须推迟项目。如果美国创新引擎不能正常运转，进步将掌握在少数大公司手中。这是立法者需要注意的一个教训，因为这些大学和小企业有助于形成美国经济的结构，并为选民创造就业机会和机会。

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.

去中心化的人工智能可以对抗这种市场集中化的趋势。该领域允许资金有限的组织跨节点共享数据和计算，开发人员将多个数据库的网络拼接在一起以提供模型和分散的 GPU 来为其提供动力。这是一种更实惠的解决方案，允许较小的参与者参与并做出贡献。它还解决了许多有关数据隐私的问题：开发人员可以在本地处理数据，从而最大限度地减少将敏感信息传输到集中式服务器的需要。这降低了数据泄露和未经授权访问的风险。

Congress's turn

轮到国会了

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.

所有这些都表明建立允许去中心化人工智能蓬勃发展的规则和法规的重要性。国会必须制定明确的数据隐私和安全法规，以保护本地处理的个人信息，并促进人工智能算法的透明度和问责制，以保护道德标准并防止去中心化系统中的偏见。

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.

立法者应考虑为去中心化人工智能制定独特的监管框架，与《算法责任法案》中的传统人工智能法规以及《区块链监管确定性法案》中涵盖的财务准则分开。新立法需要解决去中心化人工智能的特殊挑战，确保算法决策的透明度，并提供去中心化网络问责制的指导方针。此外，国会应考虑扩大《国家人工智能倡议法案》下的资助机会，以确保去中心化的人工智能项目——尤其是来自大学和小企业的项目——获得政府研发资金和税收优惠，防止大型科技公司垄断人工智能创新。沿着这些思路，国会应该明智地考虑加强反垄断执法，以阻止大公司控制关键的人工智能基础设施。

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

而且责任不仅仅落在国会的肩上。随着立法者重新关注加密货币和人工智能，现在是去中心化人工智能的支持者为该行业发声和倡导的时候了。让我们面对现实吧，该行业在传达其所做的事情以及蓬勃发展所需的内容方面并不总是做得很好。是的，这项技术很复杂，但这并不意味着倡导者不能超越技术语言，并以没有工程学位的工作人员和立法者可以理解的方式阐明它