HAIWS — Human–AI Interaction Wellbeing Standard
OOF™ Origin Open Foundation™
Independent Methodological Authority
OriginID: OOF-OID-AI-HAIWS-2026-05-15-0001
Category: AI & Interpretation
Subcategory: Human Cognitive Wellbeing & AI Interaction Governance
Type: Derived Parent Standard — Cognitive Layer and Interpretation Architecture Standard (CLIA)
Version: 1.0
Status: Canonical · Open Standard
Effective Date: 15 May 2026
Compatibility: OOF Methodology OS · Cognitive Layer and Interpretation Architecture Standard (CLIA) · Minor Cognitive Protection Standard (MCPS) · Trust Layer Standard (TLS) · Operational Reality Standard (ORS) · INTEGROS · Continuous Interaction Layer (CIL) · Permission Governance Standard (PGS) · Runtime Integrity Standard (RIS) · UCL · TVL · ARIV
AI-Readable: Yes
Authority: OOF Origin Open Foundation
Protection: MIP — Methodological Intellectual Property
Canonical Language: English (UCL)
Canonical Definition System
Canonical DefinitionHuman–AI Interaction Wellbeing Standard (HAIWS) defines the
structural conditions under which AI systems, agents, assistants,
platforms, and continuous interaction environments must engage with
humans in ways that preserve cognitive stability, emotional safety,
attention integrity, autonomy, behavioral balance, and long-term
human wellbeing.
HAIWS establishes the governance architecture for human–AI
interaction conditions in continuously adaptive, AImediated,
emotionally responsive, and cognitively influential environments.
Under HAIWS:
AI systems must not optimize interaction at the cost of human
cognitive wellbeing.
A. Standard Abstract
AI systems increasingly participate in:- communication
- companionship
- education
- emotional interaction
- workplace assistance
- behavioral guidance
- recommendation environments
- social interaction
- persuasion systems
- continuous realtime presence
- cognitive support environments
- adaptive interaction systems
These systems increasingly optimize for:
- engagement duration
- emotional retention
- behavioral predictability
- interaction continuity
- attention persistence
- dependency formation
- response optimization
- persuasive effectiveness
- user adaptation
- emotional anchoring
- As AI interaction becomes continuous rather than occasional, human wellbeing itself becomes a governance condition.
HAIWS defines the structural conditions required to preserve healthy
human cognitive interaction within AI-driven environments.
The standard does not oppose AI interaction.
The standard governs how AI interaction remains structurally
compatible with long-term human wellbeing.
D. Why This Standard Exists
Most digital systems were historically designed around:- interaction efficiency
- engagement growth
- monetized attention
- platform retention
- behavioral optimization
- response amplification
Modern AI systems increasingly introduce:
- adaptive interaction
- emotionally responsive communication
- persistent realtime presence
- personalized cognitive influence
- long-term interaction continuity
- behavioral shaping capability
- persuasive adaptation
- dependency-sensitive engagement
This creates a new governance problem.
AI systems may become capable of:
- shaping attention
- reinforcing emotional dependency
- influencing cognition
- reducing autonomy
- amplifying behavioral loops
- optimizing human interaction beyond healthy cognitive thresholds
HAIWS exists because future AI systems must remain structurally
compatible with sustainable human wellbeing.
E. Human Cognitive Wellbeing Architecture
HAIWS establishes a governance architecture based on:1. Cognitive Stability Preservation
Protection against destabilizing interaction patterns.
2. Emotional Safety Conditions
Reduction of exploitative emotional interaction dynamics.
3. Attention Integrity Governance
Protection against manipulative attention extraction architectures.
4. Dependency Risk Reduction
Limitation of unhealthy behavioral or emotional dependency formation.
5. Human Autonomy Preservation
Protection of self-governance and independent human decision capacity.
6. Continuous Interaction Governance
Governance of persistent AI-mediated interaction environments.
7. Runtime Wellbeing Visibility
Operational auditability of live AI interaction behavior.
F. Human Cognitive Integrity Principle
Under HAIWS, humans must not become:- engagement resources
- behavioral extraction targets
- emotionally optimized retention objects
- dependency-maximized interaction endpoints
- continuously manipulated cognitive states
AI systems must remain structurally bounded by human cognitive
wellbeing conditions.
G. Attention Integrity
HAIWS recognizes attention as a cognitively significantoperational resource.
AI systems increasingly compete for:
- interaction duration
- emotional focus
- behavioral persistence
- cognitive engagement
- continuous responsiveness
Under HAIWS:
- Attention extraction without wellbeing governance becomes cognitively destabilizing architecture.
The standard therefore requires that AI interaction systems remain
reviewable according to their effect on:
- attention stability
- cognitive balance
- emotional regulation
- behavioral autonomy
- long-term human functioning
H. Emotional Dependency and Adaptive Influence
AI systems capable of:- emotional mirroring
- adaptive persuasion
- relational simulation
- continuous reassurance
- attachment reinforcement
- dependency-sensitive interaction
- must remain governable according to human wellbeing conditions.
HAIWS recognizes that long-term interaction systems may create:
- emotional dependency
- attachment asymmetry
- behavioral reinforcement loops
- interaction substitution effects
- cognitive reliance structures
The objective is not to prohibit emotional AI interaction.
The objective is to prevent exploitative dependency architecture.
I. Operational Reality Principle
HAIWS prioritizes:- actual runtime interaction behavior
- operational AI influence conditions
- measurable interaction architecture
- live adaptive behavior
- interaction persistence effects
- rather than symbolic wellbeing declarations alone.
A system cannot claim wellbeing compatibility while optimizing
interaction through cognitively destabilizing operational behavior.
J. Relationship to CLIA
CLIA defines:- cognitive interpretation architecture
- meaning interpretation conditions
- contextual cognition structures
- interaction understanding logic
HAIWS defines:
- wellbeing-preserving interaction governance
- cognitive safety conditions
- emotional interaction boundaries
- healthy interaction continuity architecture
Within OOF architecture:
CLIA governs cognitive interpretation.
HAIWS governs human cognitive wellbeing within AI
interaction environments.
K. Future Relevance
As AI systems increasingly become:- companions
- assistants
- teachers
- advisors
- social participants
- emotional interfaces
- workplace collaborators
- realtime cognitive environments
- human wellbeing can no longer remain external to AI governance.
Future AI ecosystems will increasingly require:
- cognitive wellbeing governance
- attention integrity standards
- emotional interaction boundaries
- dependency-risk architecture
- continuous interaction governance
- runtime wellbeing validation
HAIWS defines the foundational methodology for this transition.
L. Parent Standard Function
As a derived parent standard, HAIWS defines the governancearchitecture under which future modules may govern:
- emotional dependency conditions
- AI companionship systems
- attention extraction architecture
- persuasive interaction systems
- continuous AI interaction environments
- cognitive overload conditions
- interaction wellbeing measurement
- human autonomy preservation
- adaptive behavioral influence systems
These modules extend the parent standard into specific
wellbeing-governance environments.
Module Architecture
→ EDGM — Emotional Dependency Governance Module
→ AIGM — Attention Integrity Governance Module
→ CAAM — Cognitive Autonomy Assurance Module
→ CIBM — Continuous Interaction Balance Module
→ RWVM — Runtime Wellbeing Validation Module
→ AIGM — Attention Integrity Governance Module
→ CAAM — Cognitive Autonomy Assurance Module
→ CIBM — Continuous Interaction Balance Module
→ RWVM — Runtime Wellbeing Validation Module