OOF™ Origin Open Foundation™

Independent Methodological Authority

OriginID: OOF-OID-AI-RAIM-2026-06-03-0001
Architecture Ecosystem: Cognitive Governance Intelligence Architecture (CLIA®)
Architecture Family: Human Cognition Governance
Operational Layer: Human Cognition Integrity Layer
Governed Space: Reality Alignment Integrity
Category: AI & Interpretation
Subcategory: Reality Alignment Governance
Type: Human Cognition Integrity Module
Parent Standard: Human Cognition Integrity Standard (HCIS)
Version: 1.0
Status: Canonical · Open Module
Origin Date: 3 June 2026

Compatibility: OOF Methodology OS ·
Human Cognition Integrity Standard (HCIS) ·
Cognitive Integrity Standard (CIS) ·
Multi-Layer Truth Validation Framework (MTVF) ·
Cognitive Reality Modeling Standard (CRMS) ·
Ethical Virtual Integrity Protocol (EVIP) ·
INTEGROS® — Integrity Standard
AI-Readable: Yes
Authority: OOF
Protection: MIP — Methodological Intellectual Property
Canonical Language: English (UCL)

Canonical Definition

Reality Alignment Integrity Module (RAIM) defines the structural conditions
under which human cognition remains materially aligned with reality, evidence,
observable conditions, and truth-valid information while interacting with AI systems,
information ecosystems, autonomous agents, synthetic content,
and future cognition-enhancing technologies.

RAIM governs reality alignment.

The module ensures that human cognition remains connected to reality
rather than progressively drifting toward assumptions, narratives, synthetic certainty,
simulated confidence, or cognitively inherited interpretations.

A system satisfies RAIM only if:

• reality alignment remains preservable
• evidence remains cognitively accessible
• assumptions remain challengeable
• synthetic certainty remains detectable
• reality drift remains governable
• cognition remains materially reality-connected

A human cognition environment that progressively disconnects cognition from reality
does not satisfy RAIM.

Module Operational Role

RAIM defines the reality-alignment governance layer of HCIS.

Its role is to preserve human cognition by ensuring that cognition remains anchored
to reality rather than inherited interpretations.

Module Operational Space

RAIM governs:

• reality alignment
• evidence alignment
• assumption governance
• reality drift detection
• synthetic certainty governance
• interpretation validation
• reality anchoring
• cognition-reality connection

The module applies wherever human cognition may become materially influenced
by information, interpretations, recommendations, or synthetic outputs.

Module Function

The module applies wherever humans must preserve:

• reality awareness
• evidence sensitivity
• assumption visibility
• truth alignment
• reality validation
• cognition legitimacy

Its function is to ensure that human cognition remains connected to reality
even when external cognitive systems become increasingly persuasive.

Minimum Implementation Framework

1. Define the Reality Alignment Object
The organization must define which cognition activities require
reality-alignment governance.

This may include:

• strategic analysis
• decision-making
• forecasting
• interpretation
• risk evaluation
• AI-assisted reasoning
• educational environments
• human-AI collaboration

2. Define Reality Alignment Conditions
The system must define the conditions under which reality alignment remains valid.

This includes:

• evidence requirements
• validation requirements
• assumption-review requirements
• reality-verification conditions
• truth-alignment requirements
• reality-anchor requirements

3. Define Reality Drift Detection Logic
The system must define how reality misalignment is identified.

This may include:

• evidence omission detection
• assumption accumulation detection
• synthetic certainty indicators
• reality-divergence analysis
• unsupported conclusion detection
• interpretation-reality comparison

4. Define Operational Response or Governance Logic
The system must define governance logic for reality-alignment degradation conditions.

Governance response may include:

• evidence review
• reality validation
• assumption challenge procedures
• truth verification
• escalation
• cognition review
• operational invalidation where required

5. Preserve Traceability & Restrict Invalid Conditions
The system must preserve reconstructable traceability of:

• evidence sources
• validation activities
• assumption reviews
• reality-verification actions
• governance interventions
• cognition decisions

A cognition environment must not remain reality-valid if cognition becomes materially
disconnected from evidence-supported reality conditions.

Use Case 1 — AI-Assisted Strategic Forecasting

Scenario
Decision-makers rely on AI-generated forecasts, simulations, and predictive models
to guide strategic planning.

Application
RAIM governs whether forecasts remain anchored to evidence and reality conditions
rather than persuasive but unsupported projections.

Result
The organization gains stronger decision legitimacy, improved reality awareness,
and reduced exposure to synthetic certainty.

Use Case 2 — Information-Rich Digital Environment

Scenario
Individuals continuously consume information generated by AI systems,
recommendation engines, media platforms, and autonomous content systems.

Application
RAIM governs reality alignment by ensuring evidence remains visible
and assumptions remain challengeable.

Result
The environment gains stronger cognitive resilience
and reduced vulnerability to reality drift.

Canonical Closing Statement

Reality Alignment Integrity Module (RAIM) defines the structural conditions
under which human cognition remains materially aligned with reality, evidence,
observable conditions, and truth-valid information while interacting with AI systems,
information ecosystems, autonomous agents, synthetic content,
and future cognition-enhancing technologies.

Human cognition cannot remain valid if it becomes disconnected from reality.
Reality alignment therefore becomes a foundational integrity condition
of governable human cognition.