HIP-290: Evidence Locker Index

Abstract

This HIP serves as the centralized index for all Responsible AI and sustainability evidence artifacts maintained by Hanzo AI. It catalogs policies, evaluation results, audit reports, model cards, and attestations that support claims made in HIP-200 and related proposals. This is the "credibility engine" that makes our AI governance framework auditable.

Purpose

Enterprise customers, regulators, and partners require:

Verifiable evidence: Documentation behind AI safety claims
Audit trails: Complete records of model development and deployment
Compliance proof: Demonstrable alignment with standards
Incident transparency: Records of issues and resolutions

This index serves as the single entry point for all AI governance evidence.

Evidence Categories

1. AI Governance Documents

Policies

Document	Description	Location	Last Updated	Owner
Responsible AI Policy	Master AI ethics framework	HIP-200	2025-12-16	AI Ethics Board
Standards Alignment Matrix	Mapping to AI standards	HIP-250	2025-12-16	AI Ethics Board
Model Risk Policy	MRM framework	HIP-201	TBD	Model Risk Committee
Data Governance Policy	Training data standards	HIP-205	TBD	Data Team
Safety Evaluation Policy	Testing requirements	HIP-210	TBD	Safety Team
Bias Testing Policy	Fairness evaluation	HIP-220	TBD	Safety Team
Human Oversight Policy	Escalation requirements	HIP-230	TBD	Operations
Incident Response Policy	Safety incident handling	HIP-200	TBD	Safety Team

Governance Records

Document	Description	Frequency	Retention
AI Ethics Board Minutes	Board-level AI decisions	Quarterly	7 years
Model Risk Committee Minutes	Deployment approvals	Monthly	7 years
Safety Team Reports	Red team findings	Continuous	5 years
Decision Log	Major AI governance decisions	As needed	Permanent

2. Model Documentation

Model Cards

Model	Version	Card Location	Last Updated
[Model A]	v1.0	`/models/model-a/card.md`	TBD
[Model B]	v1.0	`/models/model-b/card.md`	TBD

Model cards include (per Mitchell et al. standard):

Model details (architecture, training)
Intended use and users
Relevant factors and groups
Evaluation metrics and results
Training and evaluation data
Ethical considerations
Caveats and recommendations

Training Documentation

Document	Description	Per Model
Data Provenance	Training data sources and consent	Yes
Training Configuration	Hyperparameters, compute used	Yes
Carbon Footprint	Training emissions estimate	Yes
Red Team Report	Pre-deployment safety evaluation	Yes

3. Safety Evidence

Evaluation Results

Evaluation	Description	Frequency	Location
Safety Benchmarks	Standard safety eval results	Per release	Eval database
Red Team Reports	Adversarial testing results	Per release	Safety repo
Bias Audit Results	Demographic parity analysis	Per release	Fairness repo
Capability Evaluations	Dangerous capability assessment	Per release	Safety repo

Safety Metrics Dashboard

Metric	Description	Target	Status
Jailbreak success rate	% of attacks successful	<1%	Tracking
Harmful output rate	% outputs flagged harmful	<0.01%	Tracking
Hallucination rate	% outputs with factual errors	<5%	Tracking
Demographic parity	Performance gap across groups	<5%	Tracking
Response time (safety)	Time to mitigate safety issues	<4 hours	Tracking

Incident Records

Type	Description	Retention
Safety Incidents	Documented safety issues	7 years
Root Cause Analysis	Investigation findings	7 years
Remediation Actions	Fixes implemented	7 years
Post-Incident Reviews	Lessons learned	Permanent

4. Environmental Evidence

Carbon Accounting

Document	Description	Frequency	Standard
Training Emissions Report	CO2e per model trained	Per model	ML Emissions Calculator
Inference Emissions Report	CO2e from serving	Quarterly	Internal methodology
Total Carbon Footprint	Aggregate emissions	Annual	GHG Protocol
Offset Documentation	Carbon offsets purchased	Annual	Registry records

Energy Efficiency

Document	Description	Frequency
Compute Efficiency Report	Tokens per kWh trends	Quarterly
Model Efficiency Metrics	FLOPS per token by model	Per release
Data Center Selection	PUE and renewable % criteria	As updated
Hardware Lifecycle	E-waste and recycling	Annual

5. Privacy & Security Evidence

Privacy Documentation

Document	Description	Frequency
Data Processing Records	Article 30 GDPR records	Continuous
Privacy Impact Assessments	PIAs for new processing	Per feature
Consent Records	Training data consent documentation	Per dataset
Data Retention Schedules	Retention and deletion policies	As updated

Security Evidence

Document	Description	Frequency
Penetration Test Reports	External security testing	Annual
Vulnerability Assessments	Internal security scans	Quarterly
Bug Bounty Reports	External vulnerability reports	Continuous
Security Incident Reports	Documented security events	As occurred

6. External Attestations

Audits & Certifications

Type	Provider	Scope	Frequency	Status
AI Safety Audit	TBD (AI safety firm)	Safety evaluation	Annual	Planned
Bias Audit	TBD (academic partner)	Fairness assessment	Annual	Planned
SOC 2 Type II	TBD (auditor)	Security controls	Annual	Target 2025
ISO 27001	TBD (registrar)	InfoSec management	Triennial	Target 2025
ISO/IEC 42001	TBD (registrar)	AI management system	Triennial	Target 2025

Third-Party Assessments

Assessment	Provider	Frequency
Model Evaluation	HELM, Eleuther	Per release
Safety Benchmarks	Anthropic, OpenAI equivalent	Per release
Academic Review	Research partnerships	Annual

7. Public Reports

Regular Publications

Report	Description	Frequency	Audience
Transparency Report	AI governance overview	Annual	Public
Safety Report	Safety metrics and incidents	Annual	Public
Environmental Report	Carbon and energy data	Annual	Public
Model Cards	Per-model documentation	Per release	Public

Ad-Hoc Disclosures

Type	Trigger	Timeline
Safety Incident Report	Material safety issue	72 hours
Vulnerability Disclosure	Security issues	Responsible disclosure
Policy Updates	Material policy changes	30 days notice

Evidence Standards

Documentation Requirements

All evidence must include:

Title and version: Clear identification
Date: Creation/update timestamp
Author/Owner: Responsible party
Classification: Public/restricted/confidential
Retention: How long to retain
Verification level: Self-reported to audited

AI-Specific Standards

Requirement	Standard
Model documentation	Model Cards (Mitchell et al.)
Data documentation	Data Cards / Datasheets
Evaluation documentation	Evaluation harness results
Safety documentation	Red team methodology

Verification Hierarchy

Level	Description	Examples
Self-reported	Internal metrics	Performance benchmarks
Internally verified	Cross-team review	Safety evaluations
Externally reviewed	Third-party review	Academic partnerships
Externally audited	Formal audit	SOC 2, ISO
Certified	Formal certification	ISO certifications

Evidence Access

Public Evidence

Available at: docs.hanzo.ai/responsible-ai/evidence/

Responsible AI Policy (HIP-200)
Standards Matrix (HIP-250)
Model Cards (published)
Transparency Reports
Safety Benchmarks (aggregated)

Customer Evidence

Available to: Enterprise customers (under agreement)

Detailed evaluation results
Custom safety assessments
Compliance documentation
Security certifications

Restricted Evidence

Available to: Auditors, regulators (under NDA)

Full audit reports
Incident investigation details
Red team methodologies
Training data documentation

Confidential Evidence

Available to: Internal executives, board, regulators (legal requirement)

Board minutes
Legal opinions
Personnel records
Active incident investigations

Evidence Lifecycle

Creation

Evidence created per template
Technical review (if applicable)
Compliance review
Approval by designated authority
Classification and filing

Maintenance

Scheduled review per policy
Update on material changes
Version control
Cross-reference validation

Retirement

Retention period review
Legal hold check
Secure destruction or archival
Index update

Integration with AI Governance

Pre-Deployment Evidence

Required before any model release:

Post-Deployment Evidence

Required during model operation:

Production monitoring active
Incident response ready
User feedback collection
Periodic re-evaluation scheduled

Incident Evidence

Required for any safety incident:

Incident report filed (24h)
Root cause analysis (72h)
Remediation plan (1 week)
Post-incident review (30 days)

Audit Support

Request Process

External parties may request evidence via:

Customer requests: [email protected]
Audit requests: [email protected]
Regulatory requests: [email protected]

Response SLAs

Request Type	Initial Response	Full Response
Customer	2 business days	5 business days
Audit	1 business day	Per audit timeline
Regulatory	Same day	As required

Access Logging

All evidence access is logged:

Requester identity
Documents accessed
Timestamp
Purpose
Authorization

Related HIPs

HIP-200: Responsible AI Principles and Commitments
HIP-201: Model Risk Management (MRM)
HIP-205: Data Governance & Consent
HIP-210: Safety Evaluation Suite
HIP-220: Bias & Fairness Testing
HIP-230: Human Oversight & Escalation
HIP-240: Transparency Reports
HIP-250: Sustainability Standards Alignment

Changelog

Version	Date	Changes
1.0	2025-12-16	Initial draft

Evidence Locker Index