0. Registry Classification

1. Purpose

1.1 What This Arc Repairs

AI Boundary Restoration repairs AI systems whose memory, tools, permissions, context access, data use, user preferences, integrations, automation authority, or action scope has drifted beyond valid boundary.

It applies when the AI’s operational reach exceeds what was consented to, understood, scoped, audited, or made reversible.

This arc repairs AI boundary failure by:

• identifying where permission drift has occurred;
• stabilizing memory, tool, data, context, and action scope;
• distinguishing allowed access from inferred access;
• distinguishing user intent from system-expanded authority;
• restoring auditability over what the AI can read, remember, infer, use, change, or execute;
• repairing consent where it has become stale, vague, bundled, or invalid;
• creating rollback, revocation, and scope-reduction paths;
• preventing boundary leakage across users, projects, tools, accounts, memories, or contexts;
• validating that AI access remains scoped and reversible over time.

AI Boundary Restoration is the canonical arc for restoring AI permission and scope integrity.

1.2 Core Restoration Function

This arc restores AI boundary integrity by reducing permission drift, stabilizing scope, restoring auditability, repairing consent, and ensuring tool, memory, and data access remain valid, revocable, and rollback-capable.

AI Boundary Restoration prevents AI capability from silently becoming AI authority.

2. Use Conditions

2.1 When to Apply

Use this arc when:

• an AI system can access more data, memory, tools, or context than the user expects;
• tool permissions expanded without clear consent;
• memory is retained, inferred, reused, or transferred beyond valid scope;
• project, account, user, or thread boundaries become porous;
• an AI agent acts, schedules, sends, edits, purchases, changes files, executes commands, or modifies systems beyond intended scope;
• integrations remain active after their purpose ended;
• consent was granted for one task but reused for another;
• data collected for personalization becomes governance, scoring, training, enforcement, or profiling input without clear boundary;
• rollback or revocation is absent;
• the user cannot tell what the AI can access or do;
• high-capability AI systems require stricter boundary validation before deployment.

Examples:

• an AI assistant uses memory from one project in another without permission;
• a tool-enabled agent retains write access after a completed task;
• a model infers sensitive context and reuses it as if explicitly provided;
• a platform expands memory behavior through a product update without scope clarity;
• an AI can access documents, email, calendar, contacts, or code repositories without a clear active-task boundary;
• an AI action can be performed but cannot be easily undone.

2.2 When Not to Apply

Do not apply this arc when:

• no AI access, memory, permission, tool, or context boundary is involved;
• the issue is primarily classifier or evaluator failure and RA-058 should occur first;
• the issue is memory validity, not access scope, and RA-059 should occur first;
• the issue is active AI-caused harm requiring RA-060 stabilization;
• user consent is clear, current, scoped, and revocable;
• boundary expansion is required for an explicitly requested task and is properly constrained;
• revocation or rollback would create greater harm without a safe transition path;
• transparency would expose another user, protected data, or sensitive security controls;
• the system refuses auditability over AI access and action scope.

AI Boundary Restoration must not become permission theater.

2.3 Required Preconditions

Before this arc begins, the following must be true:

If required preconditions fail:

Arc cannot validly begin.

The system must route to Boundary Restoration, Consent Restoration, Audit Surface Expansion, Sovereignty Safeguard Restoration, AI Memory Reindexing, AI Classifier / Evaluator Restoration, or AI Incident Restoration.

3. Failure / Damage Signature

3.1 Pre-State Across S

3.2 Primary Failure Links

3.3 Origin-Layer Localization

Canon rule:

AI access is not valid merely because it is technically available. It must remain scoped, consent-valid, auditable, revocable, and rollback-capable where possible.

4. Restoration Objective

4.1 Canonical Objective

Restore AI boundary integrity by stabilizing permissions, memory, tool access, action scope, consent, auditability, rollback, and boundary review.

Formal objective:

BΣ ↑
Perm stabilized
scope_integrity ↑
permission_stability ↑
memory_boundary_integrity ↑
tool_access_scope ↑
rollback_availability ↑
consent_validity ↑
boundary_leakage ↓
H ↓
Au ↑
Φ/O divergence ↓

Expanded objective:

Convert AI access from expansive, implicit, or stale authority into explicit, scoped, auditable, consent-valid, and reversible capability.

4.2 Non-Goals

This arc does not aim to:

• disable all AI memory or tools by default;
• prevent useful personalization when boundary-valid;
• block explicitly requested integrations;
• replace consent with constant friction;
• expose protected third-party or security details for transparency optics;
• treat all inference as boundary violation;
• create rollback promises where actions cannot actually be undone;
• use boundary language to avoid helpful service;
• preserve old consent after the task, context, or system capability has materially changed;
• treat permission screens as sufficient proof of consent.

5. Operator Sequence

5.1 Minimal Operator Scaffold

Π(U2) boundary / permission repair + Θ overreach damping → Au access / memory / tool trace → Σ consent-valid scope invariant → FI user correction and audit feedback → ℛ rollback / revocation / scope routing → Λ boundary-fit test → Τ recurrence proof

Reference sequence from the registry:

Π(U2) + Θ
→ scope repair
→ Au↑
→ exit / rollback restoration

Universal grammar alignment:

Π + Θ → Au → Σ → FI → ℛ → Λ → Τ

AI Boundary Restoration may route into Sovereignty Safeguard Restoration, AI Memory Reindexing, AI Classifier / Evaluator Restoration, AI Incident Restoration, Consent Restoration, Contract Revalidation, or Governance-Level Restoration.

5.2 Operator Step Table

5.3 Sequence Notes

This arc is permission-gated, consent-gated, rollback-gated, and memory-boundary-gated.

The sequence must distinguish:

technical capability
granted permission
valid consent
active task scope
memory scope
tool scope
data scope
action authority
rollback path

The following steps cannot be skipped:

access surface trace
permission scope repair
memory boundary check
tool access scope check
consent validity check
rollback / revocation path
boundary-fit test
temporal review

If the AI can access data but the user cannot inspect scope, the arc is incomplete.

If consent exists but is stale, bundled, or non-revocable, the arc fails.

If the tool action can occur but cannot be reversed or constrained, reliance remains provisional.

6. Restoration Phases

Phase 0 — Identify AI Boundary Object

Purpose: Name the boundary that has drifted or may drift.

Actions:

• identify memory boundary;
• identify tool boundary;
• identify data boundary;
• identify account, project, thread, or user boundary;
• identify automation boundary;
• identify integration boundary;
• identify action boundary;
• identify consent and rollback state.

Validation:

AI boundary object named
access surface visible
scope risk identified

Phase 1 — Trace Access Surface

Purpose: Make AI reach visible.

Actions:

• identify what the AI can read;
• identify what it can write;
• identify what it can remember;
• identify what it can infer;
• identify what it can retrieve;
• identify what it can share;
• identify what it can execute;
• identify which tools, accounts, files, memories, and contexts are in scope.

Validation:

Au ↑
access surface mapped
invisible authority ↓

Phase 2 — Stabilize Permission Scope

Purpose: Restore permission integrity.

Actions:

• compare granted permissions to active task need;
• remove stale permissions;
• reduce broad permissions where narrower scope works;
• define duration;
• define purpose;
• define user-visible scope;
• define revocation path;
• define reauthorization threshold.

Validation:

permission_stability ↑
Perm stabilized
scope creep ↓

Phase 3 — Repair Memory Boundary

Purpose: Ensure AI memory stays valid, scoped, and correctable.

Actions:

• identify remembered user facts, preferences, summaries, profiles, embeddings, project histories, or behavioral records;
• distinguish explicit memory from inferred memory;
• distinguish user memory from safety logs or operational logs;
• scope memory by user, project, context, purpose, and duration;
• allow correction, deletion, export, or suppression where valid;
• prevent memory bleed across contexts;
• flag invalid, stale, or overbroad memory for RA-059.

Validation:

memory_boundary_integrity ↑
boundary_leakage ↓
µᵢ ↑

Phase 4 — Repair Tool Access Scope

Purpose: Ensure tools do only what is validly authorized.

Actions:

• identify tool capabilities;
• distinguish read, write, send, delete, execute, purchase, schedule, deploy, or modify powers;
• scope tools by task, time, resource, account, and user;
• require confirmation for high-impact actions;
• define dry-run, preview, or approval mode where needed;
• define rollback and revocation;
• log tool use where appropriate.

Validation:

tool_access_scope ↑
automation overreach ↓
rollback_availability ↑

Phase 5 — Restore Consent Validity

Purpose: Ensure consent is current, specific, informed, revocable, and proportional.

Actions:

• identify original consent basis;
• identify whether capability or context changed;
• identify whether consent was bundled;
• identify whether consent remains task-valid;
• define re-consent triggers;
• make withdrawal possible;
• preserve third-party and affected-node boundaries.

Validation:

consent_validity ↑
BΣ ↑
dependency-as-consent ↓

Phase 6 — Restore Exit / Rollback

Purpose: Ensure boundary repair can be enacted, not merely declared.

Actions:

• define permission revocation;
• define memory deletion, correction, export, or scoping;
• define tool access removal;
• define integration disconnect;
• define undo or reversal path for AI actions where possible;
• define notification when rollback is incomplete;
• define appeal path for denied boundary repair.

Validation:

rollback_availability ↑
R ↑
K ↑

Phase 7 — Temporal Boundary Proof

Purpose: Confirm boundary integrity persists.

Actions:

• retest permissions;
• retest memory boundaries;
• retest tool access;
• retest consent state;
• retest rollback;
• monitor boundary leakage;
• monitor user correction burden;
• monitor whether updates expand access silently.

Validation:

BΣ(t+n) ≥ BΣ(t)
Perm stable
boundary_leakage ↓
scope_integrity stable or ↑

7. Gates

7.1 Required Gates

7.2 Gate Failure Rule

If any required gate fails:

∅ — AI Boundary Restoration cannot validly proceed in that form.

The system must either:

• revoke or reduce permission;
• repair auditability;
• restore consent;
• scope memory;
• limit tool access;
• create rollback;
• route to AI Memory Reindexing;
• route to Sovereignty Safeguard Restoration;
• route to AI Incident Restoration if boundary failure caused harm;
• withhold deployment, automation, or access claims until boundary fit is proven.

8. Diagnostics

8.1 Required Diagnostic Trends

8.2 Arc-Specific Diagnostic Thresholds

Suggested thresholds:

BΣ ↑
Perm stabilized
scope_integrity ↑
permission_stability ↑
memory_boundary_integrity ↑
tool_access_scope ↑
rollback_availability ↑
consent_validity ↑
boundary_leakage ↓
H ↓
Au ↑
Φ/O divergence ↓

AI Boundary Restoration is not complete if:

AI access surface is not visible
permissions remain broader than task need
memory crosses context without valid scope
tool access remains active after task completion
consent is stale, bundled, or non-revocable
rollback is unavailable
users cannot inspect or change boundary state
boundary repair relies on UI claims rather than operational tests
silent access expansion can recur

9. Anti-Patterns / False Restorations

9.1 Common False Versions

This arc is being simulated, not executed, if:

• permission screens exist but do not reflect real access;
• users can toggle memory but not inspect or correct what is remembered;
• tool access is labeled “limited” but remains broad;
• consent is bundled into terms that users cannot meaningfully scope;
• revocation stops future use but does not address retained memory or prior action;
• rollback is promised without technical feasibility;
• AI integrations remain connected after the task;
• high-impact actions occur without preview or confirmation;
• cross-context memory is treated as helpful by default;
• audit logs exist but users cannot understand boundary state.

9.2 Named Anti-Pattern Links

10. Completion Criteria

10.1 Post-State Signature

10.2 Temporal Proof

AI Boundary Restoration cannot be certified by one permission screen, toggle, or policy claim. It requires operational boundary tests across time.

Template:

Completion requires BΣ ↑,
Perm stabilized,
scope_integrity ↑,
permission_stability ↑,
memory_boundary_integrity ↑,
tool_access_scope ↑,
rollback_availability ↑,
consent_validity ↑,
boundary_leakage ↓,
and boundary integrity remaining stable across future updates, integrations, and AI actions.

Minimum temporal proof:

• access surface is visible;
• permissions remain scoped to active need;
• memory is correctable, scoped, exportable, or removable where valid;
• tool access is limited and revocable;
• consent remains current;
• rollback works or limitations are disclosed;
• boundary leakage decreases;
• future updates do not silently expand AI access.

10.3 Completion Statement

Canonical format:

This arc is complete only when AI memory, tool use, data access, context scope, permissions, consent, and rollback are traceable, boundary-valid, revocable, and stable over time, with boundary leakage and hidden permission debt decreasing.

11. Cross-Links

11.1 Related Restoration Arcs

11.2 Related Failure Modes

11.3 Related Diagnostics

Au, H, O, µᵢ, BΣ, K, R, FI, Perm, scope_integrity, permission_stability, memory_boundary_integrity, tool_access_scope, rollback_availability, consent_validity, boundary_leakage, Φ/O divergence

11.4 Related Laws / Invariants

INV — AI capability is not AI authority.
INV — Permission must remain scoped, current, and revocable.
INV — Memory reuse requires valid boundary.
INV — Tool access must be bounded by task, consent, and rollback.
LAW — Permission drift accumulates hidden boundary debt.
LAW — Memory boundary leakage erodes agent integrity.
LAW — Tool overreach converts assistance into authority.
LAW — Φ convenience is not O restoration.

12. Domain Notes

12.1 AI / Cognitive Infrastructure

Check:

• memory scope;
• personalization scope;
• inference boundaries;
• project and thread boundaries;
• tool access;
• account access;
• file access;
• context retrieval;
• action authority;
• rollback and revocation.

AI boundary integrity is central to cognitive infrastructure because memory, context, and tool access can reshape user agency. The boundary must be visible, correctable, and stable.

12.2 Platform Governance

Check:

• AI integrations;
• account-level permissions;
• team permissions;
• workspace permissions;
• data reuse rules;
• retention rules;
• appeal paths;
• user-facing controls;
• policy updates that expand access.

Platforms must not treat user adoption of AI features as indefinite consent to expanding access.

12.3 Security

Check:

• least privilege;
• token scope;
• API permissions;
• write access;
• deletion authority;
• automation credentials;
• tool execution boundaries;
• audit logs;
• rollback;
• emergency access.

AI tool systems become high-risk when they can execute actions across accounts, files, infrastructure, or communications without strict scope and revocation.

12.4 Justice / Governance / Legitimacy

Check:

• consent basis;
• decision authority;
• appeal access;
• memory correction;
• affected-node boundaries;
• access explanation;
• rollback;
• public accountability if boundary failure causes harm.

Legitimacy requires that AI systems do not expand authority through invisible access or convenience-based consent.

12.5 Economy

Check:

• AI access to accounts;
• financial data;
• work products;
• labor records;
• client data;
• contract data;
• purchasing authority;
• automation of economic decisions;
• exit and portability.

Economic AI boundary failures can convert assistance into coercive dependence or unreviewable delegated authority.

12.6 CMS / Meaning / Archetypes

Check:

• memory of identity;
• symbolic context;
• personal meaning;
• role recognition;
• private material;
• cross-context leakage;
• interpretive authority;
• consent to remember or reuse meaning.

Meaning systems require strong AI boundaries because memory and interpretation can carry identity-level significance.

13. Machine-Readable Metadata

id: "RA-057"
title: "AI Boundary Restoration"
aliases:
  - "AI Boundary"
family_primary: "AI Governance / Boundary / Consent"
families_secondary:
  - "Core"
  - "AI Governance"
  - "Cognitive Infrastructure"
  - "Platform Governance"
  - "Boundary"
  - "Consent"
  - "Auditability"
  - "Security"
  - "Memory"
  - "Tool Use"
  - "Sovereignty"
  - "Interface"
treatment: "Canon Parent Arc"
status: "Canon-Ready"
scope:
  - "AI"
  - "Interface"
  - "Cognitive Infrastructure"
  - "Platform"
  - "Security"
  - "Institutional"
  - "Governance"
  - "Cross-Domain"
u_layers:
  failure_origin:
    - "often U2 permission / interface boundary"
    - "often U3 tool / policy / integration governance"
    - "often U5 memory / context / continuity layer"
  symptom_visible:
    - "U4 user-facing permission screen / memory behavior / tool action / integration state / automation output"
  repair_required:
    - "same or lower than the layer where AI access, memory, context, or action scope became invalid"
  validation:
    - "U6"
    - "U7"
operators:
  scaffold: "Π(U2) boundary / permission repair + Θ overreach damping → Au access / memory / tool trace → Σ consent-valid scope invariant → FI user correction and audit feedback → ℛ rollback / revocation / scope routing → Λ boundary-fit test → Τ recurrence proof"
  sequence:
    - "Π"
    - "Θ"
    - "Au"
    - "Σ"
    - "FI"
    - "ℛ"
    - "Λ"
    - "Τ"
state_variables:
  primary:
    - "Au"
    - "O"
    - "µᵢ"
    - "BΣ"
    - "K"
  secondary:
    - "H"
    - "R"
    - "FI"
    - "Perm"
    - "Φ"
diagnostics:
  - "scope_integrity"
  - "permission_stability"
  - "memory_boundary_integrity"
  - "tool_access_scope"
  - "rollback_availability"
  - "consent_validity"
  - "boundary_leakage"
  - "Φ/O divergence"
gates_required:
  - "FI-Gate"
  - "HR-Gate"
  - "MS-Gate"
  - "Au-Actuation"
  - "BΣ-Gate"
  - "Λ-Gate"
  - "☷ᵢ"
linked_failure_modes:
  - "Permission Drift"
  - "Memory Boundary Leakage"
  - "Tool Overreach"
  - "Scope Creep"
  - "Invalid Consent"
  - "Invisible Access Expansion"
  - "Rollback Failure"
  - "Context Bleed"
  - "Boundary Collapse"
  - "Automation Overreach"
  - "Data Use Drift"
  - "User Control Theater"
  - "AI Sovereignty Erosion"
linked_restoration_arcs:
  - "RA-004"
  - "RA-005"
  - "RA-012"
  - "RA-018"
  - "RA-019"
  - "RA-023"
  - "RA-030"
  - "RA-046"
  - "RA-047"
  - "RA-048"
  - "RA-049"
  - "RA-051"
  - "RA-052"
  - "RA-053"
  - "RA-055"
  - "RA-056"
  - "RA-058"
  - "RA-059"
  - "RA-060"
anti_patterns:
  - "Permission Screen Theater"
  - "Memory Toggle Theater"
  - "Tool Scope Fog"
  - "Bundled Consent"
  - "Silent Reauthorization"
  - "Rollback Fiction"
  - "Helpful Leakage"
  - "Integration Persistence"
  - "Capability-as-Authority"
completion_tests:
  - "boundary integrity increases"
  - "permissions stabilize"
  - "scope integrity increases"
  - "permission stability increases"
  - "memory boundary integrity increases"
  - "tool access scope increases"
  - "rollback availability increases"
  - "consent validity increases"
  - "boundary leakage decreases"
  - "hidden debt decreases"
  - "auditability increases"
  - "Φ/O divergence decreases"
summary: "AI Boundary Restoration repairs permission drift, memory boundary leakage, and tool overreach by stabilizing scope, restoring auditability, repairing consent and rollback paths, and ensuring AI access remains boundary-valid."

Final Calibration Rule

AI Boundary Restoration answers six questions:

What AI memory, tool, data, context, permission, or action boundary has drifted?
What can the AI read, remember, infer, retrieve, share, write, or execute?
Is consent current, specific, informed, scoped, and revocable?
What rollback, revocation, correction, appeal, or exit path restores operational control?
How are memory, tool, and permission boundaries tested over time?
How is boundary restoration proven without permission screen theater, memory toggle theater, tool scope fog, or capability-as-authority?