Behavioral AI Governance Infrastructure focused on execution-time governance, runtime accountability, behavioral drift observability, and replay-capable governance evidence for AI systems operating across time.

Time turns behavior into infrastructure.
Behavior is the most honest data there is.

Canonical Standards
        ↓
Runtime Governance
        ↓
Governance Telemetry
        ↓
Replay Evidence
        ↓
Continuous Assurance
        ↓
Deployment Survivability

• Behavioral drift detection
• Decision Boundary enforcement
• Stop Authority orchestration
• Governance telemetry
• Runtime observability
• Continuous assurance
• Replay-capable evidence
• Longitudinal accountability
• Deployment survivability
• Governance continuity

HHI treats governance as operational runtime infrastructure rather than static documentation.

Core operational questions:

• Can systems remain observable during execution?
• Can humans intervene during escalation?
• Can telemetry survive migration and restart?
• Can governance evidence remain replayable?
• Can accountability persist across orchestration changes?

HHI governance infrastructure maintains interoperability with:

• NIST AI RMF
• ISO/IEC 42001
• EU AI Act
• OECD AI Principles
• CAISI governance testing models
• Enterprise SIEM interoperability patterns

{ "event_id": "", "timestamp": "", "actor": "", "session_id": "", "decision_boundary": "", "behavioral_drift_score": "", "escalation_level": "", "intervention_status": "", "stop_authority": "", "action": "", "outcome": "", "evidence_hash": "", "runtime_source": "" }

Operational requirements:

• Replayable
• Exportable
• Checksum-bound
• Machine-readable
• Longitudinally observable
• Deployment portable

• Runtime survivability
• Governance continuity
• Replay persistence
• Portable evidence infrastructure
• Continuous assurance automation
• Deployment portability
• Governance observability

HHI emerged from longitudinal behavioral observation, sustained interaction with AI systems over time, and the need for governance systems capable of preserving accountability during execution.

The work focuses on:

• continuity
• accountability
• replayability
• behavioral traceability
• governance during execution
• preserving operational evidence across time

• Canonical Source: https://github.com/Hollow-house-institute/Hollow_House_Standards_Library
• DOI: https://doi.org/10.5281/zenodo.20044740
• ORCID: https://orcid.org/0009-0009-4806-1949
• GitHub Organization: https://github.com/Hollow-house-institute