Behavioral Attribution Module - (BAM)
OOF™ Origin Open Foundation™
Independent Methodological Authority
OriginID: OOF-OID-AIG-BAS-BAM-2026-06-26-0003
Architecture Ecosystem: Structured Reality Standards™
Architecture Family: AI Governance Architecture (AIG®)
Operational Layer: AI Behavioral Governance Layer
Governed Space: Behavioral Attribution
Category: AI Governance
Subcategory: AI Behavioral Governance
Type: Behavioral Auditability Standard Module
Parent Standard: Behavioral Auditability Standard (BAS)
Version: 1.0
Status: Canonical · Open Module
Origin Date: 26 June 2026
Compatibility: OOF Methodology OS · AI Governance Architecture (AIG®) · Governance Architecture (GOA™) · Accountability Governance Architecture (AGA™) · Operational Reality Architecture (ORA™) · Cognitive Governance Intelligence Architecture (CLIA®) · Memory Governance Intelligence Architecture (MGIA™)
AI-Readable: Yes
Authority: OOF
Protection: MIP™ — Methodological Intellectual Property
Canonical Language: English (UCL)
Canonical Definition System
Canonical DefinitionBehavioral Attribution Module (BAM) defines the structural conditions under
which AI behavior can be accurately attributed to its originating AI system,
autonomous agent, human participant, governance authority, operational
process, or external influence throughout the complete behavioral lifecycle.
BAM governs behavioral attribution.
The module establishes the foundational conditions required to ensure that
every significant AI behavioral activity has a clearly identifiable origin,
responsible actor, governance relationship, and attributable execution path.
Behavior may be reconstructed.
Behavior must also be attributable.
BAM governs that attribution.
Module Operational Space
BAM governs:- behavioral attribution
- behavioral ownership
- behavioral origin identification
- actor attribution
- authority attribution
- Human-AI attribution
- multi-agent attribution
- governance attribution
The module applies wherever AI behavior must be linked to a specific origin,
responsible entity, or governance authority.
Module Function
The module applies wherever systems must preserve:- attributable AI behavior
- identifiable behavioral origin
- traceable governance ownership
- accountable behavioral execution
- governance-valid attribution
- trustworthy behavioral records
Its function is to ensure that every significant AI behavior can be reliably
associated with the entity, authority, system, or process that produced or
authorized it.
Minimum Implementation Framework
1. Define the Behavioral Attribution ObjectThe organization must define which AI behaviors require attribution.
This may include:
- autonomous decisions
- Human-AI interactions
- recommendations
- robotic actions
- multi-agent activities
- delegated decisions
- escalation activities
- safety-critical behaviors
2. Define Attribution Conditions
The system must define the information required to establish behavioral
attribution.
This includes:
- originating AI system
- responsible authority
- delegated permissions
- operational context
- governance relationship
- execution identity
3. Define Attribution Failure Detection Logic
The system must identify attribution failures.
This may include:
- unknown behavioral origin
- ambiguous ownership
- missing execution identity
- broken attribution chain
- conflicting governance ownership
- governance-invalid attribution
4. Define Operational Response or Governance Logic
Governance response may include:
- attribution review
- ownership verification
- governance investigation
- authority reassessment
- accountability escalation
- behavioral correction
- operational invalidation where required
5. Preserve Traceability & Restrict Invalid Conditions
The system must preserve reconstructable traceability of:
- attribution records
- governance ownership
- authority relationships
- behavioral reviews
- intervention history
- resulting behavioral states
An AI behavioral environment must not remain auditability-valid if materially
significant behavioral attribution cannot be reconstructed, reviewed,
validated, preserved, or governed.
Use Case 1 — Multi-Agent Financial Platform
ScenarioSeveral autonomous AI agents collaborate to evaluate investment opportunities
before issuing a final recommendation.
Application
BAM attributes each behavioral contribution to the specific AI agent,
delegated authority, governance role, and final decision owner.
Result
The organization strengthens accountability, improves governance transparency,
reduces attribution ambiguity, and supports independent auditability.
Use Case 2 — Human-AI Manufacturing Environment
ScenarioA collaborative manufacturing system combines human decisions with autonomous
robotic behavior during production.
Application
BAM attributes each operational behavior to either the human operator,
autonomous robot, supervisory AI, or governance authority.
Result
The organization improves accountability, simplifies incident investigation,
strengthens governance oversight, and increases trust in Human-AI
collaboration.
Canonical Closing Statement
Behavioral Attribution Module (BAM) defines the structural conditions underwhich AI behavior can be accurately attributed to its originating AI system,
autonomous agent, human participant, governance authority, operational
process, or external influence throughout the complete behavioral lifecycle.
Behavior that can be reconstructed and verified must also have a clearly
identifiable origin. Behavioral Attribution therefore becomes the third
operational condition of Behavioral Auditability Standard within AI Governance
Architecture (AIG®).