Vol.2 - A Web of Sharing Trust-Responsibility Toward a Trustless Future
Standards Exploration | Public Review Materials
This page hosts stable and planned publications released to support standards discussion, regulatory learning, and governance research.
All materials published here are informative and non-normative.
They do not constitute certification schemes, regulatory guidance, compliance determinations, or deployment approval.
Scope of Volume 2 — Access PoD & Access-Mode
Volume 2 of A WEB of Sharing Trust–Responsibility Toward a Trustless Future expands the Policy of Developments – Access PoD initiative by introducing a practical, execution-aware view of AI governance.
The focus is on how trust, accountability, and governance signals are engineered, observed, and interpreted over time, rather than relying solely on:
static documentation,
one-off audits, or
declarative compliance claims.
Volume 2 introduces Access-Mode, a reasoning-orchestration method that governs how AI systems reason about governance materials across learning, operational analysis, and inspection contexts.
Current publications (stable and public review)
The following papers and releases are currently available:
Paper A — Governance Authority & Trust Semantics
Public Review Draft (Standards Exploration)Paper B — Feasibility & Governed Execution
Public Review Draft (Standards Exploration)Paper C — Onboarding, Containment, and Operationalization
Public Review Draft (Standards Exploration)Paper D — Governance Stress-Testing & Ethical Evaluation
Published as Planned (Standards Exploration) to support early discussion among policymakers, standards bodies, researchers, and system designers.Paper E — Access-Mode Method (APOD-TR-006, Version E)
Stable, non-normative method paper defining reasoning posture discipline (ID_1, ID_2, ID_3) and validation practices for AI-assisted governance.Access-Mode ID_1 — Core (Learning)
Live working release providing learning-only modules and examples for disciplined governance reasoning prior to operational or inspection use.Access-Mode ID_2 — Operational / Runtime Reasoning
Live, mode-specific working release formalizing structured operational governance sessions under stress. Provides scenario-based, uncertainty-aware reasoning discipline (including optional baseline/variant comparison) for examining fragility, authority drift, and escalation logic before inspection posture is invoked.
Planned working releases
The following mode-specific working releases are planned, in alignment with APOD-TR-006 (Version E):
Access-Mode ID_3 — Inspection (Review & Standards Reasoning) (planned)
Inspection-oriented reasoning for preparing governance artifacts for review, interpretation, and standards discussion.
These working releases will:
be issued independently,
preserve strict reasoning posture discipline, and
provide applied examples without modifying or extending the Access-Mode method.
Reading guidance
Method authority is defined by Paper E (Access-Mode Method).
Artifact lifecycle interpretation is explained in Version E.2.
Mode-specific working releases provide applied examples, not new method definitions.
Readers should treat all materials on this page as inputs for learning, discussion, and exploration, not as determinations of correctness, compliance, or readiness.
Volume 2 — Core Papers & Artifacts
🔹 Version A — Core Governance Framework (Authoritative Reference)
📄 Download Paper (PDF) & Artifacts link to GitHub
APOD-TR-002 — Volume 2, Version A
🔹 Version B — Architecture-Specific Extension (Reference Implementation)
📄 Download Paper (PDF)
APOD-TR-003 — Volume 2, Version B
🔹 Version C — Onboarding & Operational Transition (Public Review Draft)
📄 Download Paper & Artifacts link to GitHub
APOD-TR-004 — Volume 2, Version C
🔹 Version D — Governance Stress-Testing and Ethical Evaluation - Planned (Standards Exploration)
📄 Download Paper & Artifacts link to GitHub
APOD-TR-005 — Volume 2, Version D
🔹 Version E — Access-Mode (Method paper)
📄 Download Paper & Artifacts link to GitHub
APOD-TR-006 — Volume 2, Version E
GitHub Releases:
🔹 v1.0-Access-Mode — Reasoning Orchestration for AI Governance
📦 v1.0-Access-mode (Method) — Version E
https://github.com/Access-PoD/access-pod-artifacts/releases/tag/v1.0-access-mode
🔹 Access-Mode ID_1 — Core (Learning)
📦 This release publishes Access-Mode ID_1 — Core (Learning) as a standalone, learning-only working release.
https://github.com/Access-PoD/access-pod-artifacts/releases/tag/ID_1-core
🔹 Access-Mode ID_2 — Operational / Runtime Reasoning (Download paper)
Companion to Version E — Operational Governance Sessions and Stress Discipline
📦 This release publishes Access-Mode ID_2 as a standalone, operational-only working release.
https://github.com/Access-PoD/access-pod-artifacts/releases/tag/ID_2-Access
🔹 v1.0 Workshop — Designing Governance-Ready AI Outputs
📦 Workshop Release (Facilitated Professional Learning Framework)
https://github.com/Access-PoD/access-pod-artifacts/releases/tag/v1.0-workshop
🔹 v1.1 Workspace — Structured Inspection Environment
📦 Workspace Release (Artifacts A + B)
https://github.com/Access-PoD/access-pod-artifacts/releases/tag/v1.1-workspace
Introduction to each paper
Volume 2 — Version E - Reasoning Orchestration for AI Governance
(Method Paper — Standards Exploration)
Version E addresses a different class of governance failure than prior releases:
how AI systems reason when interacting with governance materials, and how that reasoning can silently shift, collapse, or over-assert authority without explicit controls.
While earlier versions establish governance authority (Version A), execution feasibility (Version B), onboarding and operational transition discipline (Version C), and governance stress-testing under uncertainty (Version D), Version E focuses on the reasoning process itself — not models, not execution, and not outcomes.
Version E introduces Access-Mode, a non-normative, model-agnostic method for reasoning posture orchestration, emphasizing:
explicit separation of learning, operational analysis, and inspection reasoning,
project-level discipline that prevents silent mode mixing over time, and
validation practices (including intentional misalignment testing) that expose reasoning fragility without asserting correctness or trust.
Version E treats reasoning as a governable activity.
It constrains how AI systems explain, analyze, and prepare governance materials — without redefining governance authority, assurance semantics, or compliance logic.
Version E is subordinate to Version A and complementary to Versions B, C, and D.
It does not introduce new governance principles, modify Compliance Star Certificate (CSC) semantics, or assert readiness, approval, or compliance.
Key point:
Trust is not created by fluent explanations.
It is preserved by making reasoning posture explicit, bounded, and reviewable before conclusions are drawn.
Volume 2 — Version D
Governance Stress-Testing & Ethical Evaluation
(Planned — Standards Exploration)
Version D addresses a critical and often untested dimension of AI governance: how governance and ethical controls behave when they are placed under pressure—before harm occurs.
While earlier versions establish governance authority (Version A), execution feasibility (Version B), and onboarding discipline (Version C), Version D focuses on stress-testing governance itself—not models, and not performance.
Version D introduces structured, non-exploitative governance stress-testing, emphasizing:
governance behaviour under adverse or uncertain conditions,
ethical decision-making under ambiguity and constraint, and
evidence-based trust limitation rather than post-incident justification.
Version D treats ethics as an operational governance capability, exercised through escalation, restraint, non-decision, and accountability - rather than as a checklist or alignment label.
Version D is subordinate to Version A and complementary to Versions B and C. It does not introduce new governance principles, modify assurance semantics, or alter Compliance Star Certificate (CSC) logic.
Key point: Trust is not strengthened by passing tests.
It is strengthened by observing how governance constrains, adapts, and responds when conditions change.
📦 v1d Release (artifacts — APOD-TR-005 — Volume 2, Version D)
https://github.com/Access-PoD/access-pod-artifacts/releases/tag/v1d
Volume 2 — Version C
Onboarding & Operational Transition for Runtime AI Governance
(Public Review Draft — Standards Exploration)
Version C addresses a previously under-specified phase in AI governance:
How organizations enter runtime AI governance responsibly, without asserting trust prematurely.
Version C formalizes onboarding as a governed entry condition, emphasizing:
containment before alignment,
evidence generation before assurance, and
escalation and revocation readiness under uncertainty.
Version C is subordinate to Version A and complementary to Version B.
It does not introduce new governance principles, modify assurance semantics, or alter Compliance Star Certificate (CSC) logic.
Key point:
Trust is not granted at entry.
It is engineered, observed, and maintained—continuously—through executable governance and evidence.
📦 v1c Release (artifacts - APOD-TR-004 — Volume 2, Version C )
https://github.com/Access-PoD/access-pod-artifacts/releases/tag/v1c
Volume 2 — Version B
Architecture-Specific Extension (Reference Implementation)
Version B is an optional, exploratory extension to Version A. It demonstrates how the governance framework can be instantiated at execution depth using a real system (Q-Pathformer) as a reference only.
It does not introduce new governance authority, certification criteria, or compliance claims.
Where differences arise, Version A remains authoritative.
What it is used for
Early technical and architectural review
Feasibility assessment of runtime governance
Informed feedback ahead of future consolidated editions
📦 Access PoD — Version B (v1b) Artifacts | Public Review Draft
https://github.com/Access-PoD/access-pod-artifacts/releases/tag/v1b
Volume 2 — Version A
Core Governance Framework (Authoritative Reference)
Version A defines the architecture-agnostic governance framework for Volume 2.
It establishes how AI trust is measured using runtime evidence, rather than policy statements or one-time assessments.
What it contains
Core governance model for AI systems
Simulation AI-Powered Policies (SAPP) for pre-deployment risk discovery
Access Policy-on-Demand (PoD) as a runtime governance engine
Compliance Star Certificate (CSC) as a continuous, revocable trust signal
Alignment with ISO-style risk management and emerging AI standards
Key point:
Version A is the authoritative governance reference.
All other materials in Volume 2 are subordinate to it.
📦 Access PoD Artifact Pack – v1a (Public Review Draft)
https://github.com/Access-PoD/access-pod-artifacts/releases/tag/v1a
Canonical Artifact Packs (v1a and v1b)
Authoritative Supporting Materials
The canonical artifact packs provide the machine-readable and human-readable materials referenced by Volume 2 of A WEB of Sharing Trust–Responsibility Toward a Trustless Future.
These packs represent the authoritative governance artifacts used across the series and form the stable reference base for interpretation, inspection, and evidence discussion.
What they include
Governance evidence manifests and schemas
Compliance Star Certificate (CSC) reference structures
EU AI Act Annex VII alignment materials
Operator, reviewer, and regulator interpretation aids
Current canonical releases
v1a — Canonical artifact pack supporting Version A
v1b — Canonical artifact pack supporting Version B
Key point
These artifact packs are authoritative.
They are not replaced, modified, or superseded by any workspace, workshop, or Access-Mode working release.
Note on workspace layout
The canonical artifact packs (v1a and v1b) are presented in a consistent, inspection-friendly layout within the v1.1-workspace release for convenience.
The v1.1-workspace provides a deterministic review environment only.
It is not a canonical artifact pack and does not replace, modify, or supersede the authoritative v1a and v1b releases.
v1.1 Workspace
Structured Inspection & Public Review Environment (Non-Canonical)
The v1.1 workspace provides a deterministic, inspection-ready environment for reviewers who want to explore how the Volume 2 artifacts fit together in practice.
What it contains
Canonical artifact packs (v1a and v1b) in a consistent layout
A governance harness supporting fetch, verify, and inspection workflows
No modification of canonical artifacts
Key point:
The v1.1 workspace is not a canonical artifact.
Canonical authority remains with v1a and v1b.
v1.0 Workshop
Facilitated Governance Reasoning & Professional Learning Framework (Non-Canonical)
The v1.0 workshop provides a structured, facilitated learning environment for professionals who need to apply governance reasoning in practice, particularly under conditions of uncertainty, escalation, and ethical pressure.
It is designed to build human governance capability, not to certify systems or validate compliance.
What it contains
Structured modules covering governance intent, scope, accountability, evidence discipline, and ethical decision-making
Guided exercises and case prompts focused on real-world governance scenarios
Facilitated discussion supporting escalation, restraint, and non-decision where appropriate
Reference to published Volume 2 materials for context and inspection
What it does not do
Does not modify or replace any canonical artifacts
Does not confer certification, approval, or regulatory standing
Does not define compliance criteria or assurance outcomes
Key point
The v1.0 workshop is not a canonical artifact.
Canonical authority remains with the published Volume 2 papers and their associated canonical artifacts.
The workshop exists to ensure that governance frameworks can be understood, exercised, and defended by human decision-makers, particularly when systems and organizations are under pressure.
Summary
Version A — Authoritative governance framework defining core principles, terminology, and assurance semantics.
Version B — Optional, architecture-specific illustration demonstrating execution-level feasibility without altering governance authority.
Version C — Onboarding and operational transition discipline for entering runtime AI governance under uncertainty.
Version D (planned) — Governance stress-testing and ethical evaluation, examining how governance behaves under changing and adverse conditions before harm occurs.
Version E — Method Paper (Standards Exploration) — Canonical, non-normative articulation of Access-Mode, defining reasoning posture discipline (ID_1, ID_2, ID_3) and validation practices to prevent unintentional mixing of learning, operational, and inspection reasoning in AI-assisted governance.
Access-Mode ID_1 — Core (Learning) — Live, mode-specific working release providing learning-only modules and examples for disciplined governance reasoning prior to operational or inspection use.
Access-Mode ID_2 — Operational / Runtime Reasoning — Live, mode-specific working release formalizing structured operational governance sessions under stress. Provides scenario-based, uncertainty-aware reasoning discipline (including optional baseline/variant comparison) for examining fragility, authority drift, and escalation logic before inspection posture is invoked.
v1a / v1b artifacts — Canonical supporting materials aligned to Versions A and B.
v1.1 workspace — Deterministic inspection and review environment provided for exploration and analysis (non-canonical).
v1.0 workshop (planned) — Facilitated professional learning framework developing governance reasoning, evidence discipline, and accountable decision-making required to apply all versions in practice.
Together, these materials support a structured transition from static, documentation-led AI compliance toward staged, posture-disciplined governance — progressing from learning (ID_1), to operational stress reasoning (ID_2), and, where required, to structured inspection (ID_3). This architecture enables continuous, evidence-aware governance development while remaining non-normative and suitable for public review and standards exploration.