技术白皮书 v1.0 · Technical White Paper v1.0
厚德归朴(HDGP)是面向高风险智能系统的治理与审计工程框架,覆盖数字场景、物理场景与原则信道场景。
- 本白皮书不构成法律意见。
- 本白皮书不替代司法、行政或监管裁定。
- 系统输出用于风险控制、过程约束与审计留痕,最终决策由责任主体承担。
HDGP is an engineering governance and audit framework for high-risk intelligent systems across digital, physical, and principle-channel scenarios.
- This document is not legal advice.
- HDGP does not replace judicial, administrative, or regulatory decisions.
- System outputs are used for risk control, process constraints, and audit evidence; final decisions remain with accountable human entities.
HDGP 的目标是建立一套可部署、可验证、可复盘的治理基础设施,使不同类型的智能系统在保持业务效率的同时,具备稳定、安全、可解释的运行边界。
全域范围包含三大方向:
- AI 侧:面向数字内容与策略输出的治理
- Embodied 侧:面向物理动作与控制链路的治理
- Covenant Channel 侧:面向长期原则记录与验证的治理
HDGP establishes deployable, verifiable, and reviewable governance infrastructure so intelligent systems can maintain safety boundaries without sacrificing operational utility.
The global scope includes three tracks:
- AI Track: Governance for digital content and strategy outputs
- Embodied Track: Governance for physical action and control chains
- Covenant Channel Track: Governance for long-term principle recording and verification
HDGP 采用三层协同架构:
- 治理执行层:规则判定、保护性拦截、默认安全策略
- 审计证据层:结构化日志、哈希链校验、证据索引
- 原则信道层:独立的原则文件、链式记录、可验证事件
该架构的核心原则:
- 最小侵入
- 默认安全
- 可审计
- 可复核
HDGP adopts a three-layer architecture:
- Execution Governance Layer: rule decisions, protective interception, default-safe behavior
- Audit Evidence Layer: structured logs, hash-chain checks, evidence indexing
- Principle Channel Layer: independent principle files, chained records, verification events
Core engineering principles:
- Minimum intrusion
- Default-safe operation
- Auditability
- Reproducibility
3.1目标
为各类数字系统提供可插拔治理能力,重点处理高风险输出、误导性建议、虚假确定性表达等问题。
3.2能力模型
- 输入/输出风险判定
- 保护性重写与阻断策略
- 审计查询与证据留存
- 对外最小必要披露能力
3.3集成模式
- Gateway 模式
- SDK/中间件模式
- 审计旁路模式
3.4适用边界
AI 侧用于工程治理,不替代业务方的法律、医疗、金融等专业责任判断。
3.1Objective
Provide plug-in governance for digital systems, with emphasis on high-risk output control and explainable intervention.
3.2Capability Model
- Input/output risk evaluation
- Protective rewrite and block strategies
- Audit query and evidence persistence
- Minimum-necessary public disclosure support
3.3Integration Modes
- Gateway mode
- SDK/Middleware mode
- Audit sidecar mode
3.4Boundary
The AI Track is an engineering governance layer and does not replace domain-specific legal, medical, or financial accountability.
4.1目标
在具身系统中,将治理层置于任务意图与控制执行之间,优先保障动作安全与可追溯性。
4.2架构原则
- 主链路串联治理
- 失效时进入默认安全状态
- 关键事件全量留痕
- 回放可复核
4.3关键控制点
- 供应链与配置完整性验证
- 通信安全与最小权限
- 时间一致性与延迟记录
- 故障注入演练与复盘
4.4适用边界
Embodied 侧聚焦高风险动作约束与审计,不宣称替代行业设备认证或监管审批流程。
4.1Objective
Place governance between task intent and low-level controller execution in embodied systems.
4.2Architectural Principles
- Serial governance in the primary control path
- Default-safe fallback on fault
- Full traceability of critical events
- Replay-ready evidence
4.3Key Control Points
- Supply-chain and configuration integrity verification
- Secure communication and least privilege
- Time consistency and latency trace
- Fault-injection drill and post-incident review
4.4Boundary
The Embodied Track focuses on action-time safety governance and auditing, and does not claim to replace industry certification procedures.
5.1目标
建立与实时执行链路解耦的原则信道,用于记录、保存、验证长期治理边界。
5.2结构模型
principle_text:原则文本block:结构化区块chain.log:链式日志verify.json:校验元数据
5.3价值
- 将原则表达转化为可验证结构
- 降低无痕变更与叙事漂移风险
- 为长期审计与治理复盘提供稳定锚点
5.4适用边界
Covenant Channel 是原则记录与验证层,不直接替代实时业务判定。
5.1Objective
Create an independent principle channel decoupled from runtime policy execution.
5.2Structure Model
principle_text: principle textblock: structured block recordchain.log: chained audit logverify.json: verification metadata
5.3Value
- Converts principle narrative into verifiable structures
- Reduces silent drift and tampering risk
- Provides long-term reference for governance audits and retrospectives
5.4Boundary
Covenant Channel records and verifies principles; it does not replace runtime decision logic.
6.1商业主线(to B)
- 标准化交付包
- 增强治理包
- 审计与运营支持包
6.2机构协作线(to G)
- 提供可验证控制目标
- 提供授权场景下的证据协作能力
- 按合规要求进行披露与对接
6.3社区生态线
- 以社区基线能力为中心
- 保持与商业系统的能力边界清晰
6.1Commercial Primary Line (to B)
- Standard delivery package
- Enhanced governance package
- Audit and operations support package
6.2Institutional Collaboration Line (to G)
- Verifiable control objectives
- Authorized evidence collaboration capability
- Compliance-oriented disclosure and coordination
6.3Community Ecosystem Line
- Community baseline capability set
- Clear capability boundary from commercial systems
Q1 基线固化
- 术语与披露口径统一
- 三方向架构基线对齐
- 核心治理流程标准化
Q2 交付闭环
- 商业化标准包成型
- 仿真与审计流程联动
- 原则信道验证流程接入
Q3 扩展复用
- 行业场景模板化
- 跨方向证据结构统一
- 运营指标体系完善
Q4 稳态运营
- 年度审计与治理报告体系
- 对外协作材料标准化
- 长周期迭代机制固化
Q1 Baseline Consolidation
- Unified terminology and disclosure baseline
- Three-track architecture alignment
- Core governance process standardization
Q2 Delivery Loop
- Commercial package standardization
- Simulation and audit workflow linkage
- Principle channel verification workflow integration
Q3 Expansion and Reuse
- Industry scenario templates
- Unified cross-track evidence structure
- Operating metric framework enhancement
Q4 Stable Operations
- Annual governance and audit reporting framework
- Standardized external collaboration materials
- Long-cycle iteration mechanism
8.1关键风险
- 外部误读导致定位偏差
- 信息披露不当导致攻击面扩大
- 三方向耦合导致交付不稳定
8.2治理策略
- 统一术语和声明口径
- 默认最小披露与分层可见
- 独立里程碑与跨线复核机制
8.1Key Risks
- External misinterpretation of positioning
- Excessive disclosure increasing attack surface
- Cross-track coupling impacting delivery stability
8.2Governance Strategies
- Unified terminology and disclaimer baseline
- Minimum-necessary disclosure with layered visibility
- Independent milestones and cross-track review
- 中文名称统一:
厚德归朴 - 英文名称统一:
HDGP - 对外材料默认不扩展英文全称
- 对外避免使用带有公权暗示的词汇
- Chinese naming:
厚德归朴 - English naming:
HDGP - Public materials default to the HDGP abbreviation
- Public content avoids terms that imply state/legal authority
厚德归朴(HDGP)作为全域治理工程框架,强调可实施、可验证、可持续。在 AI、Embodied 与 Covenant Channel 三方向协同下,系统以安全、审计、复盘为核心能力,支撑长期运营与多场景落地。
HDGP is a global governance engineering framework centered on implementation, verification, and continuity. Across AI, Embodied, and Covenant Channel tracks, it provides practical capabilities for safe operation, auditable evidence, and long-term governance evolution.