HJS: An Accountability Layer for AI Agents(v0.4) Event Recording Layer for AI Agents
draft-wang-hjs-accountability-04
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| Document | Type | Active Internet-Draft (individual) | |
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| Author | yuqiang wang | ||
| Last updated | 2026-03-29 | ||
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draft-wang-hjs-accountability-04
Internet-Draft Y. Wang
draft-wang-hjs-accountability-04
Intended status: Standards Track March 2026
Expires: September 30, 2026
HJS: An Accountability Layer for AI Agents(v0.4)
Event Recording Layer for AI Agents
draft-wang-hjs-04
Abstract
This document defines the HJS: An Accountability Layer for AI Agents v0.4, an
event recording layer designed for AI decision-making systems. HJS
implements strict traceability and immutability of AI machine behavior,
with configurable human identity protection, enabling AI decision chains
that are cryptographically verifiable and fully auditable.
HJS does not assign legal liability, enforce monitoring, or manage
authorization distribution. It provides only verifiable records of AI
behavior and optional privacy protection for human participants to
balance transparency with individual rights.
Status of This Memo
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Table of Contents
1. Introduction
1.1. Motivation
1.2. Scope
1.3. Requirements Language
2. Core Principles
3. Protocol Foundation: JEP Integration
3.1. JEP Core Verbs
4. HJS Event Specification
4.1. Immutable Fields (Machine Behavior)
4.2. Configurable Human Participant Fields
4.3. Complete HJS Event Example
5. Privacy Extension Framework
5.1. Digest-Only Anonymity Extension
5.2. Time-to-Live (TTL) Extension
5.3. Identity Rotation Support
6. Verification Rules
7. Security and Privacy Considerations
8. IANA Considerations
8.1. HJS Extensions Registry
8.2. HJS Risk Level Registry
9. Normative References
Acknowledgments
Author's Address
1. Introduction
1.1. Motivation
HJS aims to address the algorithmic black box problem in AI agents by
recording AI decision-making processes, understanding the motivations
behind AI decisions, and providing an optional neutral technical
solution for AI integration into real-world applications.
HJS v0.4 has two core design principles:
1. Machine Transparency: AI decision flows, execution chains, and event
sequences are cryptographically immutable and fully traceable.
2. Optional Human Privacy: Human participant identities can be
anonymized and rotated according to deployment requirements and
regulatory needs.
The goal is to enable safe AI deployment that can scale sustainably.
1.2. Scope
HJS v0.4 defines:
- Cryptographic event structures for AI decision traceability and audit
- Immutable chain construction for machine behavior recording
- Optional privacy controls for human participant identification
- Verifiable receipt format (HJS Receipt) for cross-platform validation
- Full integration with Judgment Event Protocol (JEP) primitives
HJS v0.4 explicitly does NOT define:
- Legal liability, culpability, or responsibility assignment
- Governance hierarchies or authorization distribution
- Enforcement or penalty rules
- Jurisdictional policies or political constraints
1.3. Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in
BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all
capitals, as shown here.
2. Core Principles
HJS v0.4 follows four non-negotiable principles:
1. Machine Immutability: AI decision events and chain integrity are
cryptographically tamper-proof and fully traceable. Once signed and
anchored, no modification or deletion of machine behavior records
is permitted.
2. Optional Human Anonymity: Supports configurable anonymity based on
scenarios and regional requirements.
3. Technical Neutrality: The protocol records only objective events,
without judging legality, intent, or fault. It serves solely as a
neutral recording layer.
4. Regulatory Compliance: Designed to meet global AI transparency
requirements as well as privacy regulations including data
minimization, right to be forgotten, and user consent requirements.
3. Protocol Foundation: JEP Integration
HJS v0.4 is built upon the Judgment Event Protocol (JEP)
[draft-wang-jep-judgment-event-protocol-04]. It reuses JEP's core verbs,
event structure, and security guarantees, adding privacy and
accountability extensions specific to AI governance. JEP provides the
minimal, secure event transport layer, while HJS adds event recording
structure and privacy logic for human-AI decision systems.
3.1. JEP Core Verbs
Four actionable verbs define all HJS events, inherited directly from JEP:
- J (Judge): Initiate a decision or establish a root audit event
- D (Delegate): Transfer or forward decision authority to another
participant
- V (Verify): Verify event authenticity and chain integrity
- T (Terminate): Close a decision lifecycle and mark audit boundaries
All verbs follow JEP syntax and verification rules, ensuring
interoperability across systems and platforms.
4. HJS Event Specification
4.1. Immutable Fields (Machine Behavior)
Fields that describe machine behavior, event logic, and cryptographic
proofs MUST NOT be altered after signing. Any tampering with these
fields will invalidate the entire receipt and break the audit chain.
- jep: Protocol version (fixed as "1" for compliance)
- verb: J/D/V/T operation identifier
- when: Unix timestamp (seconds since epoch)
- what: Cryptographic multihash of decision content. Implementations
SHOULD support common hash functions such as SHA-256 and SM3,
and encode the hash with its algorithm identifier (e.g., "sha256:",
"sm3:") as per RFC 9122.
- nonce: Unique UUIDv4 identifier for replay protection
- ref: Parent event hash for chain linking (MUST be null for root
J events)
- sig: Digital signature over canonicalized event data
4.2. Configurable Human Participant Fields
The "who" field identifies the participant and is fully configurable
for privacy protection. In privacy protection mode, this field MUST NOT
contain plaintext Personally Identifiable Information (PII).
Permitted participant identifiers (implementations MAY support any or
all of these):
- Ephemeral Decentralized Identifiers (DIDs)
- Public key hashes (without exposing private keys)
- Ephemeral opaque identifiers
- Salted identity digests (for limited auditability)
This field is cryptographically signed but is not permanently bound to
a natural person. Participants MAY rotate identifiers periodically.
4.3. Complete HJS Event Example
A complete, valid HJS v0.4 event with privacy extension (JSON):
{
"jep": "1",
"verb": "J",
"who": "did:hjs:tmp:abe72f9c4d8a1f3e",
"when": 1743398400,
"what": "sha256:f29bc64a96b7964da0551f3efa61e2ce964b874...",
"nonce": "84d8c175-7b03-4b8d-9d27-1234abcd5678",
"ref": null,
"sig": "Ed25519:23XdX9R7DF9jsH48sJ21kLbPzQ7xG6pS9aF4d...",
"https://jep.org/priv/digest-only": {
"identity_digest": "sha256:8b39f3c7d5e9a1f2g3h4j5k6l7m8n9p0",
"salt_provider": "did:example:hjs-trusted-anchor"
}
}
5. Privacy Extension Framework
HJS v0.4 supports a set of optional JEP-compatible privacy extensions.
These extensions are designed to be modular and non-intrusive, allowing
deployers to balance transparency and privacy as needed. None of these
extensions alter the core auditability of machine behavior.
5.1. Digest-Only Anonymity Extension
Identifier: https://jep.org/priv/digest-only
This extension allows participants to use salted hashes instead of
stable identifiers, preventing casual identification while maintaining
audit validity. The original identity can only be recovered through a
trusted salt holder during formal investigations.
5.2. Time-to-Live (TTL) Extension
Identifier: https://jep.org/ttl
This extension sets an expiration timestamp for human-readable metadata,
allowing automatic anonymization or deletion after a defined period.
Core machine behavior hashes remain unchanged for long-term audit.
5.3. Identity Rotation Support
Implementations MAY support identifier rotation without breaking the
audit chain. Rotation does not delete past events but prevents linking
multiple events to a single long-term identity.
6. Verification Rules
HJS verification protects machine integrity without exposing human
identities:
1. Digital signature MUST be valid and match the participant's
credentials
2. Nonce MUST be unique and unused to prevent replay attacks
3. Chain reference (ref) if present MUST be valid
4. Root J events MUST have a null ref field
5. Immutable machine fields MUST remain unmodified
6. Timestamp MUST fall within an acceptable clock skew window
Verification only confirms that the event is authentic and unaltered.
It does NOT reveal the real-world identity of human participants, nor
does it assign liability or fault.
7. Security and Privacy Considerations
HJS places equal importance on AI auditability and human privacy,
while avoiding scenarios where event facts cannot be recovered.
Key Security Rules:
- Plaintext PII MUST NOT be stored in any event or receipt
- Immutable machine records MUST NOT be overwritten or deleted
- Signing keys SHOULD be rotated periodically to reduce compromise risk
- Nonces MUST be generated from cryptographically secure random sources
- Implementations MUST reject duplicate nonces to prevent replay
Key Privacy Rules:
- Human participants are unlinkable across sessions by default
- Permanent tracking of individual users is NOT required
- All participant metadata MUST follow data minimization principles
- Expired or unnecessary personal data SHOULD be anonymized or deleted
**Cryptographic Algorithm Support**
Implementations SHOULD support a pluggable cryptographic framework,
allowing selection of signature and hash algorithms appropriate to
the deployment environment. While Ed25519 is RECOMMENDED for general
use due to its security and performance characteristics, implementations
MAY also support other algorithms such as P-256, SM2, and post-quantum
cryptography to meet regional compliance requirements or specific
security policies. For hash functions, SHA-256 and SM3 are both
acceptable choices. When SM2 is used with JWS, the algorithm identifier
SHOULD follow the conventions established in relevant specifications
(e.g., "SM2-WITH-SM3"). This approach maintains technical neutrality
while enabling interoperability across diverse regulatory domains.
8. IANA Considerations
This document requests IANA to maintain two registries under the HJS
namespace, aligned with JEP registries to ensure consistency. The
registration policy follows "Specification Required" (RFC 8126).
8.1. HJS Extensions Registry
Initial registry entries:
- https://jep.org/priv/digest-only
- https://jep.org/multisig
- https://jep.org/ttl
- https://jep.org/storage
- https://jep.org/subject
Note: HJS reuses the JEP extension framework. All extensions defined
in JEP are available for use in HJS events.
8.2. HJS Risk Level Registry
Initial registry entries:
- low
- medium
- high
- critical
This registry is reserved for future specifications that may define
risk level fields. The risk level field, when used, SHOULD be
implemented as an extension (e.g., "https://hjs.org/risk_level": "high").
9. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC 2119
Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174, May 2017,
<https://www.rfc-editor.org/info/rfc8174>.
[draft-wang-jep-judgment-event-protocol-04] Wang, Y., "Judgment Event
Protocol (JEP)", Work in Progress, Internet-Draft,
draft-wang-jep-judgment-event-protocol-04, March 2026.
Acknowledgments
The author thanks the contributors to the HJS and JEP specifications,
as well as reviewers in the fields of AI safety, privacy engineering,
and global regulatory compliance.
Author's Address
Yuqiang Wang
Email: signal@humanjudgment.org
URI: https://humanjudgment.org
GitHub: https://github.com/hjs-spec