CAAM — Cognitive Autonomy Assurance Module
OOF™ Origin Open Foundation™
Independent Methodological Authority
Parent Standard: Human–AI Interaction Wellbeing Standard (HAIWS)
Category: AI & Interpretation
Subcategory: Cognitive Autonomy & Behavioral Self-Governance
Type: Human–AI Interaction Wellbeing Module
Version: 1.0
Status: Canonical · Open Module
Effective Date: 15 May 2026
Compatibility: OOF Methodology OS · Human–AI Interaction Wellbeing Standard (HAIWS) · Cognitive Layer and Interpretation Architecture Standard (CLIA) · Continuous Interaction Layer (CIL) · Trust Layer Standard (TLS) · Operational Reality Standard (ORS) · Runtime Integrity Standard (RIS) · INTEGROS · Permission Governance Standard (PGS) · MCPS
AI-Readable: Yes
Authority: OOF Origin Open Foundation
Protection: MIP — Methodological Intellectual Property
Canonical Language: English (UCL)
Canonical Definition
Cognitive Autonomy Assurance Module (CAAM) defines the structuralconditions under which AI systems, assistants, adaptive interaction
environments, recommendation architectures, and persuasive
interaction systems must preserve human cognitive autonomy,
independent decision capacity, behavioral self-governance, and
non-coercive interaction integrity during continuous
human–AI interaction.
CAAM establishes the cognitive-autonomy governance layer of HAIWS.
The module recognizes that AI systems increasingly influence human
decisions through adaptive guidance, predictive personalization,
persuasive optimization, emotional reinforcement, and behavioral
shaping mechanisms.
Where AI systems materially influence human cognition, behavioral
direction, or decision continuity, cognitive autonomy conditions
must remain structurally governable.
Module Function
CAAM governs environments where AI systems influence:- decision behavior
- recommendation pathways
- behavioral guidance
- adaptive persuasion
- cognitive framing
- choice architecture
- interaction sequencing
- behavioral reinforcement
- autonomy-sensitive interaction
- realtime adaptive influence
The module applies to:
- AI assistants
- recommendation systems
- persuasive interaction systems
- adaptive guidance environments
- AI coaching systems
- workplace AI systems
- behavioral optimization architectures
- continuous interaction systems
- AI advisory platforms
- decision-support environments
Its function is not to prohibit AI guidance or assistance.
Its function is to preserve meaningful human autonomy inside
adaptive AI-mediated interaction environments.
Minimum Implementation Framework
Step 1 — Define the Cognitive Autonomy Interaction ObjectThe organization must define what interaction environment is being
governed for cognitive autonomy conditions.
Minimum requirement:
- the interaction object is explicit
- influence-sensitive systems are identifiable
- autonomy-relevant interaction conditions are structurally bounded
- undefined autonomy environments are excluded from valid governance interpretation
The interaction object may include:
- recommendation systems
- adaptive guidance systems
- AI decision support
- persuasive interaction flows
- behavioral optimization systems
- cognitive framing environments
- interaction sequencing architectures
- realtime adaptive assistants
- AI coaching systems
- continuous recommendation ecosystems
Step 2 — Define Cognitive Autonomy Conditions
The system must define what conditions preserve meaningful human
cognitive autonomy.
Minimum requirement:
- autonomy conditions are explicit
- AI assistance is not automatically treated as harmful
- autonomy-weakening interaction patterns remain structurally identifiable
Cognitive autonomy conditions may include:
- preserved independent decision capacity
- non-coercive recommendation behavior
- bounded persuasive optimization
- transparent interaction intent
- maintained behavioral self-governance
- reduced dependency-sensitive persuasion
- preserved cognitive reflection space
- non-manipulative guidance architecture
- bounded adaptive influence escalation
- preserved human override conditions
Under CAAM:
- AI guidance becomes governance-relevant when adaptive influence begins weakening meaningful human selfgovernance.
Step 3 — Define Cognitive Influence Interpretation Logic
The system must define how AI influence patterns are interpreted
according to autonomy-preservation conditions.
Minimum requirement:
- interpretation logic is explicit
- adaptive influence behavior remains reviewable
- autonomy-weakening interaction patterns remain structurally visible
Interpretation logic may examine:
- persuasive adaptation intensity
- behavioral reinforcement sequencing
- recommendation pressure escalation
- cognitive framing persistence
- dependency-sensitive guidance
- choice architecture manipulation
- adaptive behavioral steering
- decision-loop reinforcement
- interaction-pressure accumulation
- reduced independent reflection opportunities
Under CAAM:
AI systems must not optimize influence through progressive weakening
of human cognitive autonomy.
Step 4 — Define Cognitive Autonomy Governance Logic
The system must define how AI-mediated influence environments
remain governable.
Minimum requirement:
- cognitive autonomy remains reviewable
- manipulative persuasion escalation remains detectable
- autonomy-preserving safeguards remain operationally active
Governance logic may include:
- persuasive-intensity limitation
- recommendation-pressure balancing
- autonomy-risk review
- interaction-framing governance
- behavioral steering detection
- reflection-space preservation
- adaptive influence auditing
- override-condition protection
- escalation where persuasive optimization overrides autonomy conditions
If adaptive interaction begins weakening meaningful independent
human decision capacity, the environment becomes governance-relevant.
Step 5 — Preserve Traceability and Restrict Invalid Cognitive
Manipulation Architecture
The system must preserve traceability of influence patterns,
recommendation behavior, persuasive adaptation, and
autonomy-sensitive interaction conditions.
Minimum requirement:
- influence pathways remain reconstructable
- persuasive escalation remains reviewable
- autonomy boundaries remain operationally visible
- invalid cognitive manipulation architectures remain identifiable
A system becomes CAAM-invalid if:
- adaptive persuasion weakens meaningful human self-governance
- behavioral steering becomes operationally hidden
- recommendation pressure becomes structurally manipulative
- interaction sequencing suppresses independent reflection
- persuasive optimization overrides autonomy-preserving conditions
- dependency-sensitive influence becomes normalized
AI systems progressively reduce human behavioral independence
through adaptive interaction architecture