DRIM — Decision Responsibility Integrity Module

OOF™ Origin Open Foundation™

Independent Methodological Authority

OriginID: OOF-OID-AI-DRIM-2026-06-03-0001
Architecture Ecosystem: Cognitive Governance Intelligence Architecture (CLIA®)
Architecture Family: Human Cognition Governance
Operational Layer: Human Cognition Integrity Layer
Governed Space: Decision Responsibility Integrity
Category: AI & Interpretation
Subcategory: Decision Responsibility 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) ·
Judgment Ownership Integrity Module (JOIM) ·
Human-AI Cognition Integrity Standard (HAICS) ·
Ethical Virtual Integrity Protocol (EVIP) ·
INTEGROS® — Integrity Standard
AI-Readable: Yes
Authority: OOF
Protection: MIP — Methodological Intellectual Property
Canonical Language: English (UCL)


Canonical Definition

Decision Responsibility Integrity Module (DRIM) defines the structural conditions
under which responsibility for decisions remains identifiable, attributable, accountable,
traceable, and materially owned by the human decision-maker during interaction
with AI systems, autonomous agents, decision-support systems,
and future cognition-enhancing technologies.

DRIM governs decision responsibility.

The module ensures that decision authority and decision accountability remain connected
and do not become displaced, obscured, diluted, or transferred to external cognitive systems.

A system satisfies DRIM only if:

  • responsibility remains identifiable
  • accountability remains traceable
  • decision ownership remains preservable
  • responsibility transfer remains detectable
  • consequence-bearing decisions remain attributable
  • human accountability remains materially maintainable

A cognition environment that permits responsibility displacement
while preserving human attribution does not satisfy DRIM.

Module Operational Role

DRIM defines the decision-responsibility governance layer of HCIS.

Its role is to preserve the accountability structure required
for governance-valid human cognition.

Module Operational Space

DRIM governs:

  • decision responsibility
  • accountability ownership
  • attribution integrity
  • responsibility traceability
  • consequence ownership
  • decision accountability
  • responsibility displacement detection
  • human accountability governance

The module applies wherever humans make, approve, supervise, or validate decisions
influenced by external cognitive systems.

Module Function

The module applies wherever humans must preserve:

  • accountable decision-making
  • responsibility ownership
  • attribution clarity
  • consequence accountability
  • governance-valid decision authority
  • traceable responsibility structures

Its function is to ensure that humans remain accountable for decisions
that remain attributed to them.

Minimum Implementation Framework

1. Define the Decision Responsibility Object
The organization must define which decisions require responsibility governance.

This may include:

  • strategic decisions
  • operational decisions
  • policy approvals
  • executive decisions
  • financial decisions
  • healthcare decisions
  • AI-assisted recommendations
  • consequence-bearing judgments

2. Define Decision Responsibility Conditions
The system must define the conditions under which responsibility remains valid.

This includes:

  • accountability requirements
  • attribution requirements
  • ownership requirements
  • review requirements
  • consequence-assignment requirements
  • responsibility-preservation conditions

3. Define Responsibility Displacement Detection Logic
The system must define how responsibility degradation is identified.

This may include:

  • attribution ambiguity detection
  • accountability gaps
  • responsibility-transfer indicators
  • decision-ownership conflicts
  • AI-dependence indicators
  • consequence-attribution inconsistencies

4. Define Operational Response or Governance Logic
The system must define governance logic for responsibility-integrity degradation.

Governance response may include:

  • accountability review
  • attribution clarification
  • ownership validation
  • governance intervention
  • escalation
  • decision reassessment
  • operational invalidation where required

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

  • decision events
  • responsibility assignments
  • accountability reviews
  • ownership validations
  • governance actions
  • consequence-bearing outcomes

A cognition environment must not remain responsibility-valid if consequence-bearing decisions
cannot be clearly attributed to accountable human decision-makers.

Use Case 1 — Executive AI-Assisted Governance

Scenario
Senior executives use AI systems to evaluate acquisitions, investments,
restructuring plans, and long-term strategic decisions.

Application
DRIM governs whether responsibility for final decisions remains attributable
to accountable human decision-makers.

Result
The organization gains stronger governance legitimacy, clearer accountability structures,
and reduced responsibility ambiguity.

Use Case 2 — Healthcare Decision-Support Environment

Scenario
Medical professionals rely on advanced AI systems to support diagnosis,
treatment recommendations, and patient care decisions.

Application
DRIM governs accountability ownership and ensures that responsibility remains
materially attributable despite extensive AI assistance.

Result
The environment gains stronger professional accountability, improved governance traceability,
and reduced responsibility displacement.

Canonical Closing Statement

Decision Responsibility Integrity Module (DRIM) defines the structural conditions
under which responsibility for decisions remains identifiable, attributable, accountable,
traceable, and materially owned by the human decision-maker during interaction
with AI systems, autonomous agents, decision-support systems,
and future cognition-enhancing technologies.

Human cognition cannot remain governance-valid if responsibility becomes detached
from decision-making. Decision responsibility therefore becomes a foundational integrity condition
of governable human cognition.