为欧盟AI法案中的监管沙盒设计可操作流程与技术评估框架
Operationalising AI Regulatory Sandboxes: Activities, Requirements, and Technical Assessment under the EU AI Act
- 将沙盒流程拆解为29个具体环节，区分核心与扩展沙盒模式
- 提出15项基础设施要求，确保高风险AI系统合规测试可执行
- 开源配置工具支持各机构搭建可信的AI监管环境，适合政策制定者和开发者
随着AI技术进入高风险领域，系统化评估日益重要。欧盟《人工智能法案》引入了人工智能监管沙盒（AIRS），在监管机构监督下为初创企业和中小企业提供创新与合规平衡的测试环境。然而，当前评估方法分散、测试缺乏标准、开发与监管反馈不畅等问题突出。本文系统化运作AIRS生命周期：将沙盒流程划分为29项具体活动，涵盖参与前指导、申请、准备、参与、退出及退出后监控；并区分以监管监督为核心的“核心沙盒”与融合结构化技术测试的“扩展沙盒”，后者通过人工智能技术沙盒（AITS）实现。基于此，提炼出15项基础设施与治理要求，每项均对应具体活动，并与法案第9-15条中对高风险系统的提供方义务挂钩。该框架服务于多类主体：监管机构获得可执行的法律实施路径，技术专家可整合严谨评估方法，开发者则获得透明合规通道。最后提出“沙盒配置器”——一个开源框架，用于从上述要求构建AITS环境，并探讨共享技术基础如何支撑可扩展、促进创新的欧洲可信AI治理基础设施。
原文摘要 · Abstract (English)
The systematic assessment of AI systems is increasingly vital as these technologies enter high-stakes domains. To address this, the EU's Artificial Intelligence Act introduces AI Regulatory Sandboxes (AIRS): supervised environments where AI systems can be tested under the oversight of Competent Authorities (CAs), balancing innovation with compliance, particularly for startups and SMEs. Yet significant challenges remain: assessment methods are fragmented, tests lack standardisation, and feedback loops between developers and regulators are weak. This paper operationalises the AIRS lifecycle. We map the sandbox journey into 29 concrete activities, from pre-participation guidance through application, preparation, participation, exit, and post-participation monitoring, and we distinguish between a Core AIRS centred on regulatory oversight and an Extended AIRS that additionally embeds structured technical testing through an AI Technical Sandbox (AITS). From this mapping we derive 15 infrastructural and governance requirements that an AITS must satisfy, each linked to the activities it supports and, for high-risk systems, to the provider obligations set out in Articles 9-15 of the AI Act. The framework aims to address multiple stakeholders: CAs gain structured workflows for applying legal obligations; technical experts can integrate robust evaluation methods; and AI providers access a transparent pathway to compliance. We conclude by outlining the Sandbox Configurator, an open-source framework intended to instantiate AITS environments from these requirements, and by discussing how a shared technical foundation can support a scalable and innovation-friendly European infrastructure for trustworthy AI governance.
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