VIM Expanded Glossary
A Shared Language for Vital Intelligence (VIM)
Purpose of This Glossary
This glossary establishes a shared, interdisciplinary vocabulary for discussing intelligence, learning, AI, and institutional change in a generative-AI era.
Many conflicts around AI, education, and governance are not disagreements about goals, but misalignments in mental models. Words such as intelligence, control, ethics, or learning are often used as if they were universal—when in fact they carry deeply different assumptions across domains.
This glossary is designed to:
reduce semantic drift
surface hidden assumptions
support discernment rather than judgment
evolve as the VIM framework evolves
It is intentionally descriptive rather than prescriptive.
Core VIM Concepts
Vital Intelligence (VIM)
A meta-model of intelligence defined as the capacity of systems to sustain learning, dignity, and viability under conditions of uncertainty and change.
VIM integrates Natural Intelligence (NI), Artificial Intelligence (AI), and Collective Intelligence (CI) as inseparable and co-evolving.
Natural Intelligence (NI)
Human intelligence understood as embodied, emotional, relational, and shaped by experience.
NI includes:
subconscious and pre-verbal models
affective and somatic signals
trauma- and stress-sensitive cognition
NI is not optimized for speed or certainty; it evolved for survival, meaning-making, and social coordination.
Artificial Intelligence (AI)
Statistical, probabilistic systems trained on historical data to generate predictions, patterns, or content.
Key characteristics:
non-authoritative
non-intentional
sensitive to context and framing
prone to hallucination and bias
Within VIM, AI is treated as an exploratory partner, not a source of truth.
Collective Intelligence (CI)
The capacity of groups, organizations, and cultures to sense, learn, coordinate, and adapt together.
CI depends on:
trust and psychological safety
communication quality
feedback and repair mechanisms
CI cannot be enforced through hierarchy alone; it must be cultivated through conditions.
Learning & Cognition
Simulationist Learning
A learning mode in which understanding emerges through modeling, experimentation, iteration, and reflection, rather than memorization or rule execution.
Simulationist learners:
test hypotheses
observe system behavior
revise mental models over time
This framing aligns with studio pedagogy, systems engineering, and learning sciences.
Mental Model
An internal representation of how a system works, often implicit and subconscious.
Mental models:
guide perception and action
are resistant to change under stress
update through experience, not instruction alone
VIM emphasizes making mental models explicit, shared, and revisable.
Discernment
Context-aware judgment guided by relational signals and system dynamics.
Discernment differs from judgment:
judgment is static and binary
discernment is adaptive and situational
Discernment is a core skill for working with AI under uncertainty.
Pause
A deliberate interruption in action or interaction that allows regulation, reflection, and re-orientation.
In VIM, pause is a design choice, not disengagement—especially critical in addictive, high-velocity media environments.
Systems & Modeling
Control-Flow Mental Model
A worldview in which systems are understood as deterministic, hierarchical, and governed by explicit rules.
Effective in stable, closed systems. Misleading for generative AI and complex social systems.
Simulation / Modeling
The practice of representing systems to explore behavior under varying conditions.
In VIM:
models are provisional
error is informative
multiple representations are encouraged
Modeling becomes a shared language across disciplines.
Attractor
A stable pattern or region in a system’s state space toward which behavior tends to converge.
In social-technical systems, attractors can be:
fear-based (compliance, silencing)
care-based (trust, learning)
Kindness functions as a learning-stabilizing attractor.
Emergence
System-level behavior that arises from interactions among components rather than from centralized control.
CI and intelligence itself are emergent phenomena.
Ethics, Kindness, and Wellbeing
Kindness (Technical Definition)
A neuro-social stabilizing condition that:
reduces threat responses
supports trust and cooperation
enables learning under uncertainty
Kindness in VIM is functional, not sentimental.
Ethics-as-Capacity
Ethics understood not as rules or checklists, but as the human capacity to navigate complex situations with care, accountability, and discernment.
This capacity degrades under chronic stress and threat.
Trauma-Informed
An approach recognizing that stress, harm, and unresolved threat shape cognition, behavior, and learning.
Trauma-informed design emphasizes:
safety
choice
agency
repair
Economics, Institutions, and Power
Wellbeing Economy
An economic framing that prioritizes long-term human and planetary viability over short-term extraction or growth.
Often contrasted with optimization-driven models.
Dominance Hierarchy
An organizational structure emphasizing control, ranking, and compliance.
Dominance hierarchies tend to:
suppress CI
incentivize fear-based behavior
stall learning under uncertainty
Nested / Relational Hierarchy
A structure in which authority and responsibility are distributed and context-sensitive, allowing feedback to flow upward and laterally.
Supports CI and adaptability.
VUCA
Volatility, Uncertainty, Complexity, Ambiguity — the prevailing operating conditions for modern institutions.
VIM is explicitly designed for VUCA contexts.
Media, Information, and AI
Information as Terrain
A framing in which information is understood as something navigated, not consumed.
Learners develop orientation skills rather than seeking certainty.
Slopaganda
Low-quality, emotionally manipulative AI-generated content optimized for attention rather than meaning.
Creates cognitive noise and undermines discernment.
AI Psychosis
A colloquial term describing disorientation, over-trust, or delusional meaning-making arising from prolonged interaction with generative systems without grounding or regulation.
Pedagogy & Practice
Synectics
A creative method using metaphor and analogy to surface hidden assumptions and support integrative thinking.
In VIM, synectics functions as a metacognitive scaffold.
MPCM (Materials–Process–Context–Meaning)
A studio-based framework for structuring learning and reflection.
MPCM aligns naturally with simulationist and experiential pedagogy.
Studio Pedagogy
A learning approach emphasizing:
making and iteration
critique and reflection
situated learning
Studio pedagogy supports NI, AI literacy, and CI simultaneously.
Extending This Glossary
This glossary is intentionally open-ended.
Future expansions may include:
discipline-specific terms (engineering, CS, arts)
modeling formalisms
governance and policy language
student-facing versions
Contributions should prioritize:
clarity over cleverness
precision over persuasion
shared understanding over authority
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