中國首部智能體規範：從自願到精準強制

🔑 增強重點摘要

• •The policy mandates 'Agent-Level Liability' (ALL), requiring developers to embed digital watermarking and immutable logging directly into the agent's core execution environment to ensure traceability in autonomous decision-making.
• •The AIP protocol integrates with China's national 'Trusted Digital Identity' (TDI) infrastructure, allowing AI agents to verify the credentials of human users and other agents in real-time before executing high-stakes transactions.
• •The regulatory framework introduces a 'Sandbox-to-Production' certification process, where agents in high-risk sectors must pass a standardized 'adversarial stress test' conducted by the China Academy of Information and Communications Technology (CAICT) before deployment.

🛠️ 技術深入

• •AIP Protocol Architecture: Utilizes a decentralized ledger for capability discovery, allowing agents to query a distributed registry of verified skills without centralized bottlenecks.
• •Execution Environment: Requires a Trusted Execution Environment (TEE) for agents handling sensitive data, ensuring that the model weights and inference logs remain encrypted during runtime.
• •Interoperability Layer: Implements a standardized JSON-RPC interface for cross-platform agent communication, specifically designed to handle asynchronous task handoffs between heterogeneous models (e.g., Huawei's Pangu and Alibaba's Qwen).
• •Auditability: Mandatory inclusion of a 'Reasoning Trace' (RT) header in all agent-to-agent communications, which logs the chain-of-thought parameters used to reach a specific decision.

🔮 前景展望AI analysis grounded in cited sources

⏳ 時間線