[论文解读] Oversight for Frontier AI through a Know-Your-Customer Scheme for Compute Providers

J. Egan, Lennart Heim|arXiv (Cornell University)|Oct 20, 2023

Blockchain Technology Applications and Security被引用 7

一句话总结

本文提出了一套面向 AI 计算提供商的 Know-Your-Customer（KYC） 方案，尤其是面向云计算服务提供商，以实现对前沿 AI 发展的有针对性的监管并完善出口管制，通过定义一个动态计算阈值和监管要求来实现。

ABSTRACT

To address security and safety risks stemming from highly capable artificial intelligence (AI) models, we propose that the US government should ensure compute providers implement Know-Your-Customer (KYC) schemes. Compute - the computational power and infrastructure required to train and run these AI models - is emerging as a node for oversight. KYC, a standard developed by the banking sector to identify and verify client identity, could provide a mechanism for greater public oversight of frontier AI development and close loopholes in existing export controls. Such a scheme has the potential to identify and warn stakeholders of potentially problematic and/or sudden advancements in AI capabilities, build government capacity for AI regulation, and allow for the development and implementation of more nuanced and targeted export controls. Unlike the strategy of limiting access to AI chip purchases, regulating the digital access to compute offers more precise controls, allowing regulatory control over compute quantities, as well as the flexibility to suspend access at any time. To enact a KYC scheme, the US government will need to work closely with industry to (1) establish a dynamic threshold of compute that effectively captures high-risk frontier model development, while minimizing imposition on developers not engaged in frontier AI; (2) set requirements and guidance for compute providers to keep records and report high-risk entities; (3) establish government capacity that allows for co-design, implementation, administration and enforcement of the scheme; and (4) engage internationally to promote international alignment with the scheme and support its long-term efficacy. While the scheme will not address all AI risks, it complements proposed solutions by allowing for a more precise and flexible approach to controlling the development of frontier AI models and unwanted AI proliferation.

研究动机与目标

• 推动监管干预以应对前沿 AI 安全与安全风险。
• 识别计算作为 AI 治理中关键的监管节点。
• 提出面向计算提供商的 KYC 方案，以识别高风险主体并实现有针对性的限制。
• 概述此类方案如何补充出口管制与国内安全法规。
• 为国际对齐与行业协作提供路径。

提出的方法

• 将 KYC 从金融领域转化为计算 provisioning，聚焦高风险的前沿 AI 发展。
• 定义一个基于 FLOP 的动态计算阈值来触发 KYC 义务。
• 明确对计算提供商的尽职调查要求（身份识别、记录、报告）。
• 主张政府能力（美国商务部）共同设计、实施与执行该方案。
• 建议国际层面的接触以对齐标准并提升长期效力。
• 提供实施路线图，包括行业咨询与潜在与出口管制的整合。

实验结果

研究问题

• RQ1 如何为计算提供商设计一个 Know-Your-Customer 方案，在不对行业造成过大负担的前提下识别高风险的前沿 AI 发展？
• RQ2 需要哪些阈值与治理机制以实现对用于前沿 AI 的云计算的有效监管？
• RQ3 此类 KYC 方案如何补充现有的出口管制与国内 AI 安全法规？
• RQ4 为确保方案的有效性与长期性，需要哪些国际协调？

主要发现

• 计算提供商能够及时掌握客户计算使用情况，从而实现有针对性的风险管理。
• 基于 FLOP 的动态阈值可以在不增加非前沿开发者负担的情况下识别前沿 AI 活动。
• 面向计算提供商的 KYC 制度能够促进风险监测、威慑和知情政策响应。
• 通过该方案可提升与出口管制及国内安全规范的整合，国际对齐有助于长期有效性。
• 金融领域的 KYC（如 BSA/AML）经验可为治理结构、执法与跨境合作提供借鉴。