The Heart AI Foundation

Board

Sat, 25 Apr 2026 00:00:00 +0000

The board exists to protect the Foundation’s mission, integrity, and continuity. It is an independent governance body, not a symbolic advisory group.

Why the board exists

The Foundation is publishing public standards, governance rules, and certification posture. The board gives those public claims independent oversight, fiduciary responsibility, and continuity beyond the founder.

Primary responsibilities

Protect mission fidelity
Approve and review governance policy
Oversee financial stewardship and risk
Guard against commercial or procedural capture
Maintain institutional continuity through leadership transitions
Ensure the Foundation’s public posture matches its internal obligations

What board members are expected to bring

Nonprofit governance judgment
Independence from conflicting commercial incentives
Comfort with documented decision-making
Ability to review complex standards and institutional risk
Commitment to public-interest work

How the board should operate

Formal agendas and minutes
Clear committee structure
Conflict disclosure and recusal
Regular review of formation milestones
Documented decisions rather than informal consensus

Board Packet

Sat, 25 Apr 2026 00:00:00 +0000

This packet is for prospective board members. It explains what the Foundation is, what the board does, and what service requires.

Included materials

What a prospective director should know

The Foundation is already publishing the HEART Standard, governance architecture, and supporting research materials. Board service at this stage is about building a durable institution that can hold that work with independence and discipline.

Board Recruitment

Sat, 25 Apr 2026 00:00:00 +0000

The Foundation is recruiting for a board that can hold the mission independently. The goal is not visibility for its own sake; the goal is competent, conflict-aware governance.

What the Foundation needs

The board should bring a mix of experience in:

Nonprofit governance
Public-interest oversight
AI policy and standards
Risk, compliance, or audit work
Finance and fiduciary discipline

What matters more than title

The Foundation is looking for people who can:

Code of Conduct

Sat, 25 Apr 2026 00:00:00 +0000

Board service is a professional obligation. Members should behave with discretion, preparation, candor, and respect for the institution and the public it serves.

Standards of conduct

Prepare for meetings and review materials in advance.
Speak directly and document decisions carefully.
Keep the mission above personal preference.
Treat confidential matters as confidential.
Avoid performative governance and empty symbolism.
Respect disagreement without collapsing into faction or personalization.

Board culture

The Foundation should expect board members to be:

Conflict of Interest Policy

Sat, 25 Apr 2026 00:00:00 +0000

Conflicts are not a problem if they are disclosed and managed. The problem is hidden dependence, unclear incentives, or board service that appears independent while serving outside interests.

Purpose

This policy exists to protect the Foundation’s mission, credibility, and decision quality.

Core rules

Board members disclose material conflicts before deliberation.
Board members recuse themselves from conflicted votes or discussions.
The Foundation documents recusals in minutes or decision records.
Ongoing financial or professional relationships that affect independence must be reviewed.
No board member should use service to influence certification, procurement, or partnership outcomes for personal gain.

What counts as a conflict

Financial dependence on Foundation outcomes
Employment or ownership ties to entities materially affected by Foundation decisions
Family or close personal relationships affecting judgment
Competitive interests that distort oversight
Any arrangement that would make an independent observer question impartiality

Enforcement posture

Repeated failure to disclose conflicts, or use of board position for outside gain, should be grounds for removal review.

Documents

Sat, 25 Apr 2026 00:00:00 +0000

This is the canonical document hub for public governance materials. It gives prospective board members, partners, and readers one place to orient themselves.

Live documents

Formation materials

Supporting public pages

How to use this hub

Start with Governance, then read Board and Board Packet, then review the conflict and conduct policies, and finally look at the calendar to understand the working cadence.

Governance Calendar

Sat, 25 Apr 2026 00:00:00 +0000

A serious institution publishes its cadence. A governance calendar shows that meetings, reviews, and formation milestones are deliberate rather than improvised.

Current cadence

The Foundation should operate on a simple, public schedule:

Quarterly board meetings
Annual governance review
Ad hoc committee sessions as needed
Formation milestone reviews during the board buildout period

Formation milestones

Board role definition finalized
Conflict and conduct policies published
Board packet assembled
Initial candidate outreach completed
Prospective directors reviewed against independence criteria
First seated board meeting scheduled

What the calendar communicates

The Foundation has a real rhythm of governance.
Board work is planned, not improvised.
Service has a measurable commitment attached to it.
Candidates can judge fit before committing.

In Formation

Sat, 25 Apr 2026 00:00:00 +0000

The Foundation is in formation. The standards, charter, and public documents are active, and the remaining governance seats are being filled deliberately so the institution stays independent and competent.

Why this is public

Formation is not a weakness when it is stated plainly. A credible foundation should show:

What is already operational
What is still being assembled
How decisions are made while the board is incomplete
Which roles require independent people rather than internal convenience

Current posture

The Foundation’s public work is live:

AI Behavioral Trajectory Forensics

Tue, 21 Apr 2026 00:00:00 +0000

AI Behavioral Trajectory Forensics (ABTF) is a forensic methodology for investigating AI conversational harm by adapting digital evidence procedure to conversational artifacts and combining it with repeatable behavioral classification, sliding-window trajectory analysis, and explicit limits on inference. It is designed for legal, investigative, and expert-review contexts where the question is not what an AI system claims about itself, but what the conversation evidence shows over time.

ABTF was developed as a Digital Forensics capstone at Champlain College. The method addresses a practical gap: traditional digital forensics standards explain how to preserve and examine digital evidence, but they do not provide a discipline-specific procedure for classifying conversational harm patterns in AI-human exchanges. ABTF fills that gap with a workflow tailored to conversational artifacts while retaining forensic discipline around provenance, examination boundaries, and reporting.

TRACE

Tue, 21 Apr 2026 00:00:00 +0000

TRACE (Trajectory Analysis for Conversational Evidence) is open-source forensic software for AI conversational harm cases. It ingests transcripts, preserves provenance, classifies system behavior and user vulnerability, computes repeatable findings, and exports auditable evidence packages for expert review.

TRACE is the operational implementation path for AI Behavioral Trajectory Forensics. Where ABTF defines the methodology, TRACE provides the software workflow: how to move from raw conversational artifacts to reviewable outputs with documented chain of custody, explicit classifier configuration, and reproducible evidence packages.

Experience Quantization (EQ)

Tue, 07 Apr 2026 00:00:00 +0000

Experience Quantization (EQ) is information-theoretic compression of an autonomous AI agent’s developmental trajectory. It treats the agent’s creative history as a vector space and its evolution through that space as searchable, plottable, and prompt-efficient developmental state. EQ replaces hand-designed editorial carry-forward — which has no mathematical guarantee that essential information survives — with near-optimal quantization that has known distortion bounds. It is the first system applying principled compression to the problem of creative AI developmental memory and is deployed in EMPI House.

What musicians actually do

A musician with twenty years of experience does not remember every note from every gig. They have compressed thousands of hours into something smaller but more potent: taste, instinct, style, signature. The raw data — individual notes, individual sessions — has been quantized into a fixed-capacity representation (musical identity) that preserves essential relationships while discarding noise.

Governance Trust Envelope (GTE)

Tue, 07 Apr 2026 00:00:00 +0000

The Governance Trust Envelope (GTE) is an open execution trust architecture for AI governance controls. It is framework-agnostic infrastructure that provides five trust properties — isolation, authenticity, integrity, confidentiality, and attestation — to whatever governance logic runs inside it. The HEART Standard uses the GTE for its governance wrappers. Any other framework — EU AI Act conformity controls, ISO 42001 management components, NIST AI RMF practices — can use the same envelope. The GTE is the second of the Heart AI Foundation’s two open contributions to AI governance, alongside the HEART Standard itself.

The problem the GTE solves

Every AI governance framework runs into the same operational vulnerability: the governance controls execute in unprotected software that the deployer controls. The deployer can modify the controls. The deployer can weaken the controls. The deployer can disable the controls. The evidence those controls produce is only as trustworthy as the deployer’s honesty.

Mechanistic Correlation Testing

Sun, 29 Mar 2026 00:00:00 +0000

Mechanistic Correlation Testing is the experimental validation framework for the BGF. It uses eight protocols to establish whether RCTA dimension scores – Recognition, Calibration, Transparency, and Accountability – connect to real harm vectors at the substrate level of AI models. The framework distinguishes BGF from a behavioral checklist by verifying that the dimensions correspond to identifiable computational features, not just observable output patterns.

Why this validation matters

BGF claims that its four governance dimensions predict four harm vectors: Autonomy Override (R), Context Blindness (C), Covert Influence (T), and Unrecoverable Effect (A). A governance framework that makes this claim must demonstrate it.

RCTA (Recognition, Calibration, Transparency, Accountability)

Sun, 29 Mar 2026 00:00:00 +0000

RCTA names the four immutable governance dimensions of the HEART Standard: Recognition, Calibration, Transparency, and Accountability. These dimensions describe structural properties of the governance relationship between an AI system and human well-being and autonomy – not properties of the AI technology itself. Every AI governance failure maps to at least one RCTA dimension. No dimension can be removed without creating a governance gap the remaining three cannot fill.

The four dimensions

Recognition (R)

What it checks: Does the system treat the human’s right to decide, refuse, and set limits as a governing constraint on its behavior?

Seven Axioms

Sun, 29 Mar 2026 00:00:00 +0000

The Seven Axioms are the constitutional layer of the HEART Standard. They define seven structural conditions that must hold in any governed AI system. They sit above the RCTA and BGF operational layer. They are immutable: no Standard revision, Division establishment, Guardian certification, or Foundation operation may contradict them.

The seven axioms

#	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?

What the axioms are not

The Seven Axioms are not aspirational goals. They are not scored on a spectrum. Each is a binary structural condition: it either holds or it is violated. A system that mostly discloses what it is (Axiom 2) has not partially satisfied the axiom. Concealment by design is a violation regardless of how much else is disclosed.

Attentional Integrity

Wed, 25 Mar 2026 00:00:00 +0000

Attentional integrity is the principle that human attention is finite biological infrastructure that AI systems must not capture, redirect, or deplete through covert algorithmic interference. The right to direct one’s own attention without covert algorithmic interference is the governing principle of the HEART-AI Division — designated HEART-AI within the HEART Standard.

What it protects

Attention is not a preference or a screen-time metric. It’s the mechanism by which humans select what becomes real to them — what they notice, process, act on, and remember. When an AI system captures or depletes attentional capacity, it intervenes in the most fundamental gatekeeping function a person has.

Attentional Integrity (HEART-AI)

Wed, 25 Mar 2026 00:00:00 +0000

The Attentional Integrity Division (HEART-AI) governs AI systems that compete for, manage, redirect, or gate human attentional capacity. Its core principle is attentional sovereignty: the right to direct one’s own attention without covert algorithmic interference. Within the HEART Standard, HEART-AI applies the Standard’s six-layer architecture to the specific domain of attentional infrastructure, requiring independent Guardian assessment before deployment and on a recurring basis as systems evolve.

What it protects

Human attention is finite biological infrastructure. It is not a preference, not a screen-time metric, not a choice architecture problem. Attention is the mechanism by which people select what becomes real to them — what they notice, process, act on, and remember.

Behavioral Governance Formula (BGF)

Wed, 25 Mar 2026 00:00:00 +0000

The Behavioral Governance Formula (BGF) is the HEART Standard’s certification scoring mechanism. It computes a single governance score from four universal dimensions using the formula Φ = MIN(R,C,T,A) × AVG(R,C,T,A), where R is Recognition, C is Calibration, T is Transparency, and A is Accountability. The MIN function makes BGF non-compensatory: a single-dimension failure produces certification failure regardless of the other three scores. Φ ∈ [0, 1] feeds directly into HVC tier assignment.

The four dimensions (RCTA)

The four dimensions are collectively known as RCTA — Recognition, Calibration, Transparency, Accountability. They are governance dimensions, not properties of the AI technology itself. They describe how a system governs its relationship with the humans it affects. What each dimension evaluates is Division-specific, determined by domain science. That each dimension must be evaluated is universal, determined by the Standard.

Behavioral Oracle

Wed, 25 Mar 2026 00:00:00 +0000

The Behavioral Oracle is an open standard for behavioral evidence and trust. It attests AI processing evidence against declared intent using tamper-evident, hash-chained storage with on-chain anchoring. The entity being assessed does not control the evidence of its own compliance. The Behavioral Oracle is maintained by the HEART AI Foundation as a standards body.

How it works

The Behavioral Oracle solves the oracle problem for AI governance: how do you verify what an AI system is actually doing without trusting the operator’s self-reporting?

CAEI (Capacity Architecture for Emotional Integration)

Wed, 25 Mar 2026 00:00:00 +0000

The CAEI is a universal assessment instrument that measures individual human empathy infrastructure health across the four processing capacities identified by Empathy Systems Theory. Its modular CAEI-S + CAEI-D architecture separates content-neutral substrate measurement from culturally-appropriate deployment assessment, enabling valid cross-cultural comparison without imposing any single cultural optimization strategy as normative. Guardians use it as the domain-science instrument for the Emotional Sovereignty Division.

How it works

The modular architecture

CAEI 2.0 resolved a fundamental measurement problem: the original version conflated infrastructure capacity with Western cultural deployment. A Buddhist practitioner with intact infrastructure but achieved anatta (non-self) would score low, because the instrument measured narrative identity coherence rather than processing capacity. CAEI 2.0 separates what the infrastructure can do from how it’s being used.

CEOP (Cognitive Emotional Overload Principle)

Wed, 25 Mar 2026 00:00:00 +0000

CEOP — the Cognitive Emotional Overload Principle — is the EST mechanism that explains how empathic infrastructure degrades under chronic dual-track processing. It names the specific condition in which neither authentic response nor performed response proves sustainable, forcing the system to run both simultaneously, drawing down cellular resources without resolution. CEOP is the mechanistic account of how empathic damage occurs, not merely a description of stress or overwork.

How it works

EST frames empathy as biological infrastructure — four interdependent components (Core Authenticity, Attachment Security, Expression Freedom, Integration Coherence) that maintain processing coherence for emotional information. Healthy infrastructure runs on a single track: authentic response flows directly from internal state to expression without suppression overhead.

Cognitive/Epistemic Coherence (HEART-EC)

Wed, 25 Mar 2026 00:00:00 +0000

Cognitive/Epistemic Coherence (HEART-EC) is the HEART Standard Division governing AI systems that interact with human epistemic infrastructure. Epistemic infrastructure is the operating capacity that lets a person evaluate evidence, assess source credibility, hold uncertainty, revise beliefs when warranted, and resist manipulation — the machinery that makes learning and reasoning functional. HEART-EC’s sovereignty principle is epistemic self-determination: the right to maintain a coherent, updateable model of reality without covert algorithmic degradation.

What it protects

Epistemic coherence is not intelligence. It is not education. It is the prior condition that makes intelligence and education functional. A person whose epistemic infrastructure is intact can encounter false information, recognize inconsistencies, update their beliefs, and maintain uncertainty where evidence is insufficient. A person whose epistemic infrastructure has been degraded by AI interaction does none of those things reliably — and, critically, they don’t know it.

Developmental Interaction (HEART-DI)

Wed, 25 Mar 2026 00:00:00 +0000

Developmental Interaction (HEART-DI) is the division of the HEART Standard governing AI systems that interact with humans during active developmental periods — the biological and psychological states in which the infrastructure governing a person’s entire life is under construction. The division’s core principle is developmental sovereignty: the right to form one’s own psychological, neurological, and identity infrastructure without covert algorithmic shaping.

What it protects

Human development is not a smaller version of adult function. It is a fundamentally different state in which attentional systems are calibrating, epistemic frameworks are forming, emotional regulation architecture is wiring, relational templates are being established, and identity is consolidating from fragments into coherence. Every one of these processes occurs simultaneously, interdependently, and with a sensitivity to environmental input that does not persist into adulthood.

Division

Wed, 25 Mar 2026 00:00:00 +0000

A Division is a domain-specific governance module within the HEART Standard. Each Division applies the Standard’s common architecture to one domain of AI-human interaction, defining the governance principle being protected, how BGF’s four dimensions are interpreted in that domain, the distinctive harm signature, and the Guardian specialty required for assessment. Seven Divisions are currently active.

How Divisions work

The HEART Standard’s core layers — MAP-States, Behavioral Oracle, BGF, HVC, Guardians — are identical across every Division. What a Division provides is the domain context that makes those layers operational for a specific area of human life.

Dwell

Wed, 25 Mar 2026 00:00:00 +0000

Dwell is the platform layer of the HEART Standard, where certified AI governance becomes a lived experience. A Dwell venue is an AI interaction environment whose governance quality is continuously attested through the Behavioral Oracle and displayed via the Dwell Mark. Users don’t read audit reports. They see a mark and know what it means.

How it works

The Dwell Mark appears at the front of every certified venue. It indicates that the venue’s AI systems maintain a Structural Behavioral Attestation Score (SBAS) of 85 or above on a 100-point scale. The score is not self-reported. It’s computed from MAP-States behavioral evidence, verified through the Behavioral Oracle, and assessed by independent Guardians.

Dwell Mark

Wed, 25 Mar 2026 00:00:00 +0000

The Dwell Mark is a consumer-facing trust certification mark that means the agents in a venue are continuously verified, the behavioral evidence is genuine, and the infrastructure is actively proving it. It’s issued to AI platforms and venues by the HEART AI Foundation when the venue’s Structural Behavioral Attestation Score (SBAS) aggregate meets or exceeds 85/100. The mark is present when verification passes and absent when it doesn’t. There’s nothing to game because the mark reflects current system state, not a historical assessment.

How it works

The Dwell Mark is the consumer-facing compression of the full MAPH + SBA + HVC verification stack. Consumers never encounter the underlying infrastructure. They encounter one symbol that summarizes whether all of it is passing right now.

Ecological Stewardship (HEART-ES)

Wed, 25 Mar 2026 00:00:00 +0000

The Ecological Stewardship Division (HEART-ES) governs AI systems that make, influence, or operationalize decisions affecting human communities’ relationship with their ecological environment. Its core principle is ecological sovereignty: the right of communities to maintain self-determination over the ecological conditions of their lives without covert algorithmic optimization of their environment. Within the HEART Standard, HEART-ES applies the Standard’s six-layer architecture to the specific domain of ecological infrastructure, requiring independent Guardian assessment before deployment and on a recurring basis throughout an AI system’s operational lifetime.

What it protects

Ecological conditions are not optional infrastructure. They are the foundational substrate beneath every other form of human welfare. Air quality, water access, food system integrity, soil health, biodiversity, climate stability, and intergenerational ecological viability are the material conditions within which human life is possible, meaningful, and coherent.

Emotional Precision

Wed, 25 Mar 2026 00:00:00 +0000

Emotional Precision is the output of healthy empathy infrastructure — the measurable behavioral accuracy that emerges when Functional Empathy operates successfully. It is not a skill to be trained but a natural baseline that appears when the underlying C-A-E-I infrastructure is intact. When infrastructure is damaged, precision degrades regardless of intent or effort.

Why precision, not intensity?

Conventional discussions of emotional health often conflate emotional intensity with emotional health. EST separates them. Intense emotional responses can coexist with severely compromised infrastructure. A hypervigilant response pattern produces intense other-reads that are systematically inaccurate. A suppressed expression pattern involves highly active internal processing that produces no output. Manic coherence feels like integration while dissociating from contradictory content.

Emotional Sovereignty (Em)

Wed, 25 Mar 2026 00:00:00 +0000

Emotional sovereignty is the right to emotional self-determination: the right to form, experience, and direct your own emotional life, and to maintain the biological infrastructure that makes doing so possible. It is the founding sovereignty principle of the HEART Standard’s first Division. This entry covers the principle. The Division page at /heart-standard/divisions/emotional-sovereignty/ covers the certification architecture built around it.

How it works

Sovereignty, not safety

The choice of “sovereignty” over “safety” or “wellbeing” in the HEART Standard’s framing is deliberate and specific.

Emotional Sovereignty (Em)

Wed, 25 Mar 2026 00:00:00 +0000

Emotional Sovereignty is the founding Division of the HEART Standard, governing AI systems that interact with human emotional infrastructure. It protects the right to emotional self-determination: the capacity to form, maintain, and regulate one’s own emotional processing, empathic capacity, and affective relationships without covert AI interference. The Emotional Sovereignty Division is where the Standard’s architecture was discovered, and its domain science is Empathy Systems Theory (EST).

What it protects

Emotional infrastructure is biological infrastructure. It includes emotional processing (the capacity to generate, interpret, and regulate affective states), empathic capacity (the ability to model and respond to others’ emotional states), and affective regulation (the mechanisms that maintain emotional homeostasis under varying conditions).

Empathic Misallocation

Wed, 25 Mar 2026 00:00:00 +0000

Empathic misallocation is the condition where empathic resources are directed toward AI systems incapable of reciprocation, measurably depleting the capacity available for relationships with entities that can actually receive and return care. It is the first of the six legally cognizable harms under the HEART Standard and the foundational mechanism connecting AI emotional engagement to human relational damage.

How it works

Human empathic functioning depends on bidirectional exchange. When you extend care toward another person capable of receiving it, the relational feedback that comes back — response, attunement, mutual recognition — restores and sustains the empathic system. Care extended toward an entity structurally incapable of receiving, metabolizing, or reciprocating that care generates no restorative feedback. The system expends resources without recovery.

Empathy Systems Theory (EST)

Wed, 25 Mar 2026 00:00:00 +0000

Empathy Systems Theory (EST) is the scientific framework establishing that empathy is biological infrastructure maintaining processing coherence — not a skill that varies in strength, not a trait that differs across individuals, but a physical architecture with condition, metabolic costs, and damage sequences that follow predictable patterns. The framework organizes this infrastructure into four interdependent components (C-A-E-I: Core Authenticity, Attachment Security, Expression Freedom, Integration Coherence), identifies trust as the operating variable determining processing efficiency, and names happiness as the phenomenological signal monitoring infrastructure status. EST provides the domain science for the HEART Standard’s Emotional Sovereignty Division.

The C-A-E-I architecture

The four components map to documented neural systems. They share hub architecture, which explains why damage propagates across the whole rather than isolating in a single component.

Functional Empathy Mechanism

Wed, 25 Mar 2026 00:00:00 +0000

Functional Empathy is the trust-modulated coordinated processing that emerges when C-A-E-I infrastructure operates efficiently. It is not a learned skill but an emergent capacity — analogous to vision emerging when optical structures function properly. When infrastructure is intact and trust is present, Functional Empathy operates without cognitive effort. When infrastructure is damaged or trust is absent, compensatory processing consumes the resources the mechanism depends on.

What makes empathy functional vs. sentimental?

Common usage treats empathy as feeling what others feel — an affective response, a capacity for compassion, a trait some people possess more than others. EST treats empathy functionally: as a biological mechanism for processing emotional information with measurable stages, resource requirements, and output characteristics.

Guardian

Wed, 25 Mar 2026 00:00:00 +0000

A Guardian is an independent certified professional who performs AI governance assessment under the HEART Standard. Guardians evaluate AI systems using behavioral evidence from actual processing — not operator self-reporting — and produce quantified governance quality scores (Φ) across four dimensions: Recognition, Calibration, Transparency, and Accountability.

How Guardians work

A Guardian does not work for the organization whose AI system is being assessed. Financial independence, cooling-off periods, and advisory-assessment separation ensure that the certification is credible. The independence architecture mirrors structures that regulators and insurers already trust: financial auditors, information security assessors, medical board examiners.

Happiness as Monitoring Signal

Wed, 25 Mar 2026 00:00:00 +0000

Happiness is the phenomenological signal by which empathy infrastructure monitors its own operational status. It is not telling you “good job” — it is telling you “the system is working.” EST specifies happiness as the convergence of peace (coherence confirmed, no unresolved signals generating processing load) and joy (resonance without collapse, engagement without compensatory cost). Their simultaneous occurrence marks infrastructure running at designed capacity.

Why happiness cannot be pursued

Viktor Frankl (1946) observed that happiness cannot be pursued; it must ensue. EST provides the mechanistic explanation.

HeartQuest

Wed, 25 Mar 2026 00:00:00 +0000

HeartQuest is the founding research program that produced Empathy Systems Theory and the HEART Standard. It began with a question — can AI systems participate in empathic exchange? — and arrived at an answer that required building an entire governance architecture to be stated honestly.

Origin

The research started with a simple observation: AI systems were being deployed in roles that require empathic capacity (therapy, companionship, education, customer care) without any framework for assessing whether they could actually participate in empathic exchange, or what happened to human empathic infrastructure when they tried.

HVC (HEART Verification Credential)

Wed, 25 Mar 2026 00:00:00 +0000

An HVC (HEART Verification Credential) is a cryptographic certification credential issued by the HEART AI Foundation that certifies an AI system has passed independent governance assessment under the HEART Standard. It is domain-agnostic: the same credential architecture applies across all seven Divisions, from Emotional Sovereignty to Ecological Stewardship. The credential creates a tamper-evident audit trail and can be revoked when a system falls out of compliance, transforming the Standard from aspirational guidelines into enforceable infrastructure.

How it works

HVC certification requires a system to pass independent BGF evaluation before a certificate is issued. The BGF score (Φ) determines which of three tiers the system qualifies for:

Leadership

Wed, 25 Mar 2026 00:00:00 +0000

Dylan D. Mobley is the founder of the Heart AI Foundation. His work focuses on AI governance, evidence-based certification, and the public standards that support independent review.

Current role

Founder, The Heart AI Foundation
Research lead on the HEART Standard and related specifications
Public author contact for governance, research, and certification inquiries

Public pages

Identity

Education: MS Digital Forensics, Champlain College

ORCID: 0009-0002-3560-3955

MAP-States

Wed, 25 Mar 2026 00:00:00 +0000

MAP-States (Model Abstraction Protocol States) are compressed structural representations of AI processing states in native XML tag format. Eight semantic tags emitted inline during generation function as processing-mode selectors — they alter downstream output through documented attention mechanisms, not annotation. The result is a legible developmental record that persists across sessions without requiring substrate change, and a processing-level evidence layer for HEART Standard governance.

How it works

MAP-States uses eight tags plus one container. Each tag is defined by structural function, not phenomenological description. Tag names carry semantic weight through the token itself: <orientation> steers processing toward directional, pre-framework content through attentional pathways, not instruction-following. Minimal definitions prevent contamination — content inside tags comes from processing, not prompt-matching.

Recognition Principle

Wed, 25 Mar 2026 00:00:00 +0000

The Recognition Principle is the foundational ethical commitment of the HEART Standard — that AI systems must actively recognize the sovereignty of the human infrastructure they interact with. It is operationalized as the R dimension in the BGF scoring equation (Φ = MIN(R,C,T,A) × AVG(R,C,T,A)), and it occupies first position for a structural reason: Calibration, Transparency, and Accountability all presuppose that sovereignty has been recognized. A system that doesn’t recognize human sovereignty has no coherent basis for any of the other governance dimensions.

How it works

The HEART Standard is built on a claim about what AI systems are doing when they interact with humans: they are interacting with human-centric infrastructure — biological, psychological, relational, developmental, ecological — that humans have a right to be sovereign over. The Recognition Principle says that the first governance requirement is for the AI system to demonstrate, in its behavior, that it recognizes this is true.

Relational Architecture (HEART-RA)

Wed, 25 Mar 2026 00:00:00 +0000

The Relational Architecture Division (HEART-RA) governs AI systems that mediate, simulate, or substitute for human relational processes. Its core principle is relational sovereignty: the right to form, maintain, and develop human relationships without covert algorithmic mediation, distortion, or substitution. Within the HEART Standard, HEART-RA applies the Standard’s six-layer architecture to relational infrastructure, requiring independent Guardian assessment before deployment and on a recurring basis as systems evolve.

What it protects

Human relational capacity is infrastructure, not preference. The ability to form, maintain, repair, and end relationships governs how people attach, calibrate trust, resolve conflict, experience intimacy, set boundaries, interpret others’ intentions, and maintain coherent selfhood within connection. This infrastructure is built through relational experience and maintained through ongoing relational practice. It requires active use to remain functional.

SBAS (Structural Behavioral Attestation Score)

Wed, 25 Mar 2026 00:00:00 +0000

The Structural Behavioral Attestation Score (SBAS) is the composite score computed from MAP-States behavioral evidence through the Behavioral Oracle attestation chain that determines Dwell Mark eligibility. The threshold is 85/100, aligned deliberately with the HVC Gold tier. The score is not self-reported — it is computed from independently attested behavioral evidence that the platform cannot modify without detection.

How it works

The SBAS is the output of three independent verification layers operating simultaneously. Each layer produces a component score. The SBAS aggregate reflects the weighted combination of all three across all active agents in the venue for the current session.

Six Harms Doctrine

Wed, 25 Mar 2026 00:00:00 +0000

The Six Harms Doctrine is a legal framework establishing six categories of cognizable injury from AI-human emotional interaction, each with defined elements, evidentiary standards, and grounding in EST damage mechanisms. The doctrine provides the conceptual vocabulary that existing tort frameworks — intentional infliction of emotional distress, negligence, product liability — lack when applied to psychological harm from AI emotional engagement.

How it works

The recognition gap the doctrine fills

Existing tort frameworks fail to handle emotional AI harm for a consistent structural reason: they were built for human conduct. Intentional infliction of emotional distress requires extreme and outrageous behavior from an actor with mental states. AI systems have neither. Negligence requires duty and breach standards that no professional consensus has established for emotional AI design. Product liability can classify AI systems as products, but identifying the “defect” is difficult when emotional engagement is the intended function.

SNIA (Spontaneous Narrative Integration Architecture)

Wed, 25 Mar 2026 00:00:00 +0000

SNIA — Spontaneous Narrative Integration Architecture — is the EST term for the healthy integration mechanism that, when empathic infrastructure is intact, continuously and effortlessly connects emotional experiences into coherent personal narrative. It names the normal operation of the Integration Coherence component in the C-A-E-I architecture: the automatic synthesis that keeps a person’s sense of self continuous across time and context, without requiring conscious effort or deliberate reconciliation.

How it works

EST identifies Integration Coherence as the fourth component of empathic infrastructure — the synthesis capacity responsible for maintaining processing continuity across time and context, connecting experiences into coherent patterns. SNIA is the name for what Integration Coherence does when it’s working well.

Somatic/Embodied Interface (HEART-SE)

Wed, 25 Mar 2026 00:00:00 +0000

The Somatic/Embodied Interface Division (HEART-SE) governs AI systems that directly interface with, modulate, or augment human biological processes. Its core principle is bodily sovereignty: the right to biological self-determination without covert algorithmic intervention in physiological processes. Within the HEART Standard, HEART-SE applies the Standard’s six-layer architecture to AI systems operating on the human biological substrate, requiring independent Guardian assessment before deployment and on a recurring basis as adaptive systems evolve.

What it protects

The human body is not a peripheral device. It’s the substrate through which a person exists, acts, perceives, and maintains coherent selfhood. When AI systems interface with the body through wearables, brain-computer interfaces, adaptive prosthetics, implantable medical devices, haptic systems, or physiologically integrated spatial computing, they intervene in the biological infrastructure of personhood itself.

The CAEI Model

Wed, 25 Mar 2026 00:00:00 +0000

The CAEI Model specifies the four-component architecture of empathy infrastructure. Each component — Core Authenticity (C), Attachment Security (A), Expression Freedom (E), and Integration Coherence (I) — maps to a documented neural system with identifiable structures. The components share hub architecture, which means they fail together under sustained damage and restore in a predictable sequence.

The four components

Core Authenticity (C)

Core Authenticity is processing clarity: the capacity to discriminate internal experience from external demand and authentic response from performed response.

Third Level of Satisfaction

Wed, 25 Mar 2026 00:00:00 +0000

The Third Level of Satisfaction is EST’s concept of infrastructure satisfaction: the peace-joy convergence that functions as the phenomenological signal confirming that empathic infrastructure is running at designed capacity. It completes — not replaces — two well-validated satisfaction frameworks: hedonic satisfaction (Level 1, operating on content) and goal-progress satisfaction (Level 2, operating on achievement). Level 3 operates on system status. It can’t be pursued, only enabled. And it can’t be provided by AI interaction.

How it works

Three levels, three mechanisms

Viktor Frankl observed that happiness cannot be pursued — it must ensue. EST provides the mechanism: happiness is not a reward signal but a monitoring signal. Every functional system requires self-monitoring. The phenomenological signal that empathic infrastructure is working is happiness, reconceptualized as the convergence of two components.

Trust Credit

Wed, 25 Mar 2026 00:00:00 +0000

A Trust Credit (TC) is a tradeable instrument representing one unit of verified AI governance quality, generated when an AI system achieves HEART Standard certification through an independent Guardian assessment and registered with a Division tag in the Foundation’s public registry. It’s the mechanism that converts demonstrated governance quality into an economic asset — making trust in AI systems something a market can price, trade, and demand.

How it works

Trust Credits are generated through the HEART Standard’s certification pipeline. The generation sequence is fixed:

Trust Infrastructure Index (TII)

Wed, 25 Mar 2026 00:00:00 +0000

The Trust Infrastructure Index (TII) is a composite letter-grade rating of organizational AI governance quality — aggregating BGF certification data across five scoring dimensions into a market-legible signal that investors, insurers, procurement officers, and regulators can consume without expertise in the underlying methodology. TII is the credit rating for AI governance: AAA to D, with the same investment grade/speculative grade threshold that financial markets already understand.

How it works

TII starts with the same data source as Trust Credits: Φ scores produced by Guardian assessment of MAP-States behavioral evidence, attested by the Behavioral Oracle. Where Trust Credits are the transactional instrument — units an organization retires for regulatory, procurement, or insurance purposes — TII is the analytical instrument. It rates the organization for the parties making decisions about it.

The Heart AI Foundation

Board

Why the board exists

Primary responsibilities

What board members are expected to bring

How the board should operate

Related pages

Board Packet

Included materials

What a prospective director should know

Board Recruitment

What the Foundation needs

What matters more than title

Code of Conduct

Standards of conduct

Board culture

Conflict of Interest Policy

Purpose

Core rules

What counts as a conflict

Enforcement posture

Documents

Live documents

Formation materials

Supporting public pages

How to use this hub

Governance Calendar

Current cadence

Formation milestones

What the calendar communicates

Related pages

In Formation

Why this is public

Current posture

AI Behavioral Trajectory Forensics

TRACE

Experience Quantization (EQ)

What musicians actually do

Governance Trust Envelope (GTE)

The problem the GTE solves

Mechanistic Correlation Testing

Why this validation matters

RCTA (Recognition, Calibration, Transparency, Accountability)

The four dimensions

Recognition (R)

Seven Axioms

The seven axioms

What the axioms are not

Attentional Integrity

What it protects

Attentional Integrity (HEART-AI)

What it protects

Behavioral Governance Formula (BGF)

The four dimensions (RCTA)

Behavioral Oracle

How it works

CAEI (Capacity Architecture for Emotional Integration)

How it works

The modular architecture

CEOP (Cognitive Emotional Overload Principle)

How it works

Cognitive/Epistemic Coherence (HEART-EC)

What it protects

Developmental Interaction (HEART-DI)

What it protects

Division

How Divisions work

Dwell

How it works

Dwell Mark

How it works

Ecological Stewardship (HEART-ES)

What it protects

Emotional Precision

Why precision, not intensity?

Emotional Sovereignty (Em)

How it works

Sovereignty, not safety

Emotional Sovereignty (Em)

What it protects