为AI运行时的每项决策提供可验证的审计记录协议
AIREP: A Protocol for Per-Decision Evidence in AI Runtime Governance
- 用签名对象记录AI决策，支持离线验证
- 通过哈希链确保记录不可篡改且可追溯
- 适合需要合规审计的AI系统开发者
本文提出一种用于记录自动化AI运行时治理决策的协议。当运行时对单个输出进行发布、阻断、延迟、删除或升级处理时，AIREP将该决策以单一签名对象形式记录，任何第三方均可离线验证，无需依赖生成该决策的运行时。记录包含在既定政策基础上的封闭动词集、输入/输出及证据的哈希引用，明确说明证据覆盖范围与不覆盖范围。记录构成基于SHA-256的哈希链，绑定各记录位置，使篡改和缺失可被重新计算检测。供应商、模型和领域特定内容被限制在可选命名空间内，机械中立性测试确保共享格式不受其影响。文中描述了参考实现和双语言一致性工具包，讨论了实现中的若干问题，如跨实现标准格式对齐、新鲜度证明及多运行时链等挑战。该格式可供任意记录治理决策的AI运行时采纳。
原文摘要 · Abstract (English)
A protocol is presented for recording the governance decisions of automated AI runtimes. When a runtime releases, blocks, defers, redacts, or escalates an individual output, AIREP records that decision as a single signed object that any party can check offline, independent of the runtime that produced it. A record carries the decision as one of a closed set of verbs under a stated policy basis, references its input, output, and evidence by hash rather than by value, and declares both what its evidence covers and what it does not. Records form a SHA-256 hash chain that binds each record to its position, so that tampering and gaps are detectable by recomputation. Vendor-, model-, and domain-specific content is confined to a single optional namespace, and a mechanical neutrality test keeps the shared format free of it. A reference implementation and a two-language conformance kit are described. Some implementation issues are considered, and problems such as alignment of the canonical form across implementations, freshness witnesses, and multi-runtime chains are exposed. The format is offered for adoption by any AI runtime that records governance decisions.
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