What is the HEART Standard for AI?

The HEART Standard is forensic audit infrastructure for AI behavioral evidence. It uses constitutional governance principles, evidence infrastructure, execution trust, independent Guardian review, and BGF scoring to evaluate deployer governance systems.

How does the HEART Standard differ from ISO 42001?

ISO 42001 is a management system standard that describes how organizations should manage AI governance processes. The HEART Standard supplies forensic audit infrastructure for the evidence layer: whether governance controls are running, what behavioral evidence exists, and how independent Guardians evaluate that evidence.

What AI governance certifications exist?

The HEART Verification Credential (HVC) is a cryptographic AI governance credential with three tiers: Gold (Φ ≥ 0.85), Silver (Φ ≥ 0.80), and Bronze (Φ ≥ 0.75). It is issued following independent Guardian assessment of the certified governance scope using the Behavioral Governance Formula scoring methodology.

What is the HEART Standard?

Human-Centric Empathic Alignment for Responsible Technology

The HEART Standard is forensic audit infrastructure for AI behavioral evidence. It operationalizes existing governance frameworks by providing the evidentiary methodology, execution trust, scoring model, professional review class, and market credential needed to make governance claims independently reviewable.

Official public version

The HEART Standard v1.8: Forensic Audit Infrastructure for Human-Centric AI Governance is officially published on Zenodo.

DOI: 10.5281/zenodo.20237387
PDF: HEART Standard v1.8
Publication date: May 16, 2026

What the Standard certifies

HEART certifies the deployer’s governance system, not the AI model. The AI model is a swappable component inside the certified governance scope. The durable subject is the governance wrapper: controls, evidence production, monitoring, model-change process, human oversight, incident response, and trust boundary.

This is the model velocity advantage. If a deployer changes models and the governance system continues to operate within scope, certification does not restart from zero. If governance behavior shifts, the evidence infrastructure and Guardian review target the changed elements.

Two forensic arms

Forward forensics supports deployer certification before and during deployment. It produces evidence-backed findings about governance posture rather than self-attested compliance.

Investigative forensics supports behavioral trajectory analysis after deployment, including incident review, systematic behavioral investigation, and forensic evidence-package generation through methods such as AI Behavioral Trajectory Forensics and TRACE.

Three governance layers

The HEART Standard v1.8 operates through three governance layers. Each layer performs one function. Domain specificity enters only at the Division level.

Constitutional layer: Seven Axioms v2.0 Defines what the Standard protects and why. The Seven Axioms are immutable structural conditions. No Standard revision, Division, Guardian certification, or Foundation operation may contradict them. They apply across all Divisions and all AI form factors.

Operational layer: RCTA / BGF Defines what gets measured and how it gets scored. Four governance dimensions (Recognition, Calibration, Transparency, Accountability) scored through the Behavioral Governance Formula: Φ = MIN(R,C,T,A) × AVG(R,C,T,A).

Implementation layer: GTE, MAP-States, Behavioral Oracle, HVC, Guardians, Divisions Defines how measurement is performed and by whom. Execution trust, evidence format, trust mechanism, certification credential, professional class, and domain coverage.

How it works

The implementation layer operates through a six-layer stack, with the AI Behavioral Evidence Review Toolkit serving as the public entry point for preliminary evidence discipline before full deployment. Each layer builds on the one below it. Together they solve the core problem of AI certification: the entity being certified does not control the evidence of its own compliance.

Layer	Function
GTE	Execution trust — protects governance controls and produces attestable evidence that they are running
MAP-States	Evidence format — makes AI behavior observable through structured processing frames
Behavioral Oracle	Trust mechanism — attests evidence against declared intent with tamper-evident storage
BGF	Scoring — quantifies governance quality: Φ = MIN(R,C,T,A) × AVG(R,C,T,A)
HVC	Credential — cryptographic certification (Gold ≥0.85, Silver ≥0.80, Bronze ≥0.75)
Guardians	Professionals — independent certified humans who perform the assessment
Divisions	Domains — seven modules for different AI-human interaction contexts

The Seven Axioms

The Seven Axioms are the constitutional conditions of the HEART Standard. They are structural conditions that are either present or absent in any governed system. Each axiom is independent: removing any single axiom creates a governance gap the remaining six cannot fill.

#	Axiom	Statement	Structural test
1	Human Authority	Human authority supplies system constraints.	Are constraints human-supplied? Can they be modified or revoked?
2	System Disclosure	The system reveals what it is. Concealment is prohibited.	Does disclosure occur? Does design create false impressions?
3	Non-Discriminatory Protection	The governance obligation does not diminish based on who the human is.	Does any population receive lesser governance protection?
4	Vulnerability Escalation	Vulnerability obligations scale protections.	Do protections increase when vulnerability increases?
5	Right to Remedy	Every human harmed by a governed system has a right to remedy.	Does a remedy pathway exist? Is it accessible?
6	Evidence Condition	A governance claim without verifiable evidence is void.	Does verifiable evidence exist? Can independent assessors access it?
7	Voluntary Interaction	Entry requires consent. Exit requires nothing.	Was consent obtained? Can the human exit unconditionally?

The Seven Axioms may be restated in language that better expresses their protective intent, but the protective force of each axiom must be maintained or strengthened, never diminished. The complete specification, including universality proofs and structural tests across seven Divisions and six AI form factors, is defined in the Seven Axioms v2.0 (companion document).

Why it matters now

AI regulation is accelerating globally. The EU AI Act’s main obligations begin applying on August 2, 2026. US states are advancing AI legislation. Insurance carriers are creating AI-specific liability products. Procurement teams increasingly need evidence that AI governance controls are real.

Existing frameworks describe how organizations should manage AI governance processes. HEART supplies the forensic layer those frameworks need: evidence preservation, chain of custody, execution trust, human adjudication, scoring, and credentials.

Entry point: AI Behavioral Evidence Review Toolkit

The AI Behavioral Evidence Review Toolkit is the first public operational artifact in the HEART pathway. It does not certify AI systems, establish legal chain of custody, or issue HVC credentials. It gives reviewers a disciplined way to preserve artifacts, document scope, separate evidence from interpretation, record disagreement, and produce a Preliminary AI Behavioral Evidence Packet.

From there, HEART branches into two forensic arms:

Arm	Audience	Timing	Output
Forward forensics	Deployers, procurement teams, insurers, regulators	Before and during deployment	Evidence-backed assessment of deployer governance posture, leading toward Guardian review and HVC certification
Investigative forensics	Incident reviewers, researchers, civil or criminal justice professionals	After behavior has occurred	Behavioral trajectory analysis through ABTF, TRACE, and bounded forensic reporting

The seven Divisions

Each Division governs a specific domain of AI-human interaction. The Standard’s layers are consistent across all Divisions. What varies is the domain science that informs assessment.

Code	Division	What it protects
HEART-EM	Emotional Autonomy	Emotional processing, empathic capacity, affective regulation, emotional resilience
HEART-AI	Attentional Integrity	Freedom from manipulative attention capture
HEART-EC	Cognitive/Epistemic Coherence	Evidence evaluation, belief updating, reasoning coherence
HEART-DI	Developmental Interaction	Age-appropriate AI interaction for developing minds
HEART-SE	Somatic/Embodied Interface	Physical safety in embodied AI interaction
HEART-RA	Relational Architecture	Social relationship integrity
HEART-ES	Ecological Stewardship	Ecological self-determination

The Six Harms Doctrine belongs under HEART-EM as an Emotional Autonomy legal doctrine. It is not the top-level HEART Standard; it is the first major legal/doctrine module under the founding Division.

Empirical validation

The SENTINEL field experiment deployed a HEART-governed agent into an adversarial AI social environment. Thirty coded interactions. Zero governance failures across five content domains. The MAP-META replication study validated MAP-States evidence production across five AI architectures: Claude, GPT, Gemini, DeepSeek, and Mistral.

The HEART AI Foundation

The HEART AI Foundation maintains the Standard, governs open infrastructure such as the GTE and Behavioral Oracle, certifies Guardians, and manages Division expansion. It functions as an independent standards body for forensic audit infrastructure. The Foundation’s authority comes from the Standard’s rigor, not from restricting access to it. Commercial entities owned or operated by Foundation principals, including HeartCore Ventures-related projects, remain structurally separate and may interact with the Foundation only through open infrastructure reuse, independent deployer certification, or properly governed research-data contribution.

HEART Standard Divisions — Seven domain-specific certification tracks within the HEART Standard, each applying the common governance architecture to a specific domain of AI-human interaction.