High-impact and potentially dangerous capabilities can and should be broken down into early warning shots long before reaching red lines. Each of these early warning shots should correspond to a precursory capability. Each precursory capability sits on a spectrum indicating its proximity to a final high-impact capability, corresponding to a red line. To meaningfully detect and track capability progress, we propose a taxonomy of dangerous capability zones (a zoning taxonomy) tied to a staggered information exchange framework that enables relevant bodies to take action accordingly. In the Frontier AI Safety Commitments, signatories commit to sharing more detailed information with trusted actors, including an appointed body, as appropriate (Commitment VII). Building on our zoning taxonomy, this paper makes four recommendations for specifying information sharing as detailed in Commitment VII. (1) Precursory capabilities should be shared as soon as they become known through internal evaluations before deployment. (2) AI Safety Institutes (AISIs) should be the trusted actors appointed to receive and coordinate information on precursory components. (3) AISIs should establish adequate information protection infrastructure and guarantee increased information security as precursory capabilities move through the zones and towards red lines, including, if necessary, by classifying the information on precursory capabilities or marking it as controlled. (4) High-impact capability progress in one geographical region may translate to risk in other regions and necessitates more comprehensive risk assessment internationally. As such, AISIs should exchange information on precursory capabilities with other AISIs, relying on the existing frameworks on international classified exchanges and applying lessons learned from other regulated high-risk sectors.

翻译：高影响力且具有潜在危险的能力可以且应当在触及红线前被分解为多个早期预警信号。每个早期预警信号应对应一项先兆能力。每项先兆能力在表征其与最终高影响力能力（即红线）接近程度的连续谱上占据特定位置。为实现对能力进展的有效监测与追踪，我们提出一种与分级信息交换框架相绑定的危险能力区域分类体系（区域化分类法），使相关机构能够据此采取行动。在《前沿人工智能安全承诺》中，签署方承诺酌情向受信主体（包括指定机构）共享更详细的信息（承诺条款VII）。基于本区域化分类体系，本文就承诺条款VII所述的信息共享机制提出四项具体建议：（1）先兆能力应通过内部评估在部署前被识别后立即共享。（2）人工智能安全研究所（AISIs）应被指定为接收和协调先兆能力信息的受信主体。（3）AISIs应建立完善的信息保护基础设施，并确保随着先兆能力在区域间移动并趋近红线时逐步提升信息安全等级，必要时可通过将先兆能力信息定密或标记为受控信息实现。（4）特定地理区域的高影响力能力进展可能转化为其他区域的风险，需要在国际层面开展更全面的风险评估。因此，AISIs应依托现有国际涉密信息交换框架，借鉴其他受监管高风险领域的经验教训，与其他AISIs开展先兆能力信息交换。