TEG-Code — Turning Emotional Complexity into AI-Ready

Emotional Intelligence in Data Form

Introducing TEG-Code

"What if machines could tell the difference between someone who's struggling and someone who's manipulating? Between a trauma response and intentional harm? Between genuine repair and performative apology?

TEG-Code makes that possible by turning emotional complexity into structured data that preserves the nuance humans need and the logic machines can process."

Why Current Emotional AI Can’t Distinguish Intent vs Impact

Most tools treat emotions like simple labels:

happy, sad, angry.

But emotional behavior lives in intent, regulation state, and impact.

That’s why:

Gaslighting often goes unnoticed.
Emotional repair is mistaken for being “nice.”
Survivors doubt themselves for years.

We need tools that track emotional safety and harm with real structure.

The deeper problem: Current AI can't distinguish between identical behaviors with completely different intentions. A child saying "I don't want to" could be healthy boundary-setting or trauma response - but systems treat them the same.

That's why gaslighting often goes unnoticed, emotional repair gets mistaken for being "nice," and survivors doubt themselves for years.

What TEG-Code Offers

Each behavior is translated into:

Color Zone (blue, orange, red, black)
Relational Intent (connect, protect, punish, control)
Pattern Type (repair cue, survival response, control tactic)
Relational Impact (builds trust, erodes safety)
Example Text (how it actually sounds or feels)

This isn’t “positive vs. negative”— It’s a gradient of intent and regulation.

How It Works

Each card is stored in JSON-LD, a web-friendly format.

That means it can be:

Parsed by machines
Queried by researchers
Expanded by therapists, coders, and survivors

Under the code is a trauma-aware emotional logic, built for systems that want to protect people—not control them.

5 Common Myths About Emotional Data

Most systems treat emotion as either too messy to model—or too simple to need depth. These myths don’t just limit technology—they distort how we see human behavior. When emotional data is misunderstood, harm gets mislabeled as harmless, empathy gets misread as weakness, and real pain gets lost in translation. TEG-Code challenges these blind spots by offering a framework that sees emotion as structured, contextual, and essential—not soft, chaotic, or optional.

A quick breakdown of how most systems misunderstand emotion—and what TEG-Code offers instead.

The Myth	Why It’s Harmful	TEG-Code’s Response
Emotions can be fully quantified	Reduces rich emotional states to numbers or scores—ignoring story, intent, and relational meaning.	Maps emotion as logic, not just data. Emotions are patterns, not metrics.
One universal model fits all	Erases cultural, neurodivergent, and trauma-based differences in emotional expression.	Builds flexibility into the model. Emotion = context × history × intent.
Emotional data is objective	Hides bias in labeling, power in framing, and context in meaning.	Makes emotional logic transparent. Shows behavior, impact, and motive—side by side.
Emotion is the opposite of logic	Devalues emotional reasoning, especially in survival or relational stress.	Frames emotion as structured logic. Defense and belonging are emotional algorithms.
Emotion models are only for therapy or AI	Excludes emotional awareness from systems that need it—like education, justice, or leadership.	Designs for systems, not silos. Emotional safety is a foundation for all human systems.

Sample Card (Gaslighting)

Intent: Control

Impact: Distorts reality

Example:

“You’re being way too sensitive. That’s not how it happened at all.”

Code version:

{
  "@context": {
    "eb": "https://emotionalblueprint.org/schema#",
    "rdfs": "http://www.w3.org/2000/01/rdf-schema#",
    "xsd": "http://www.w3.org/2001/XMLSchema#"
  },
  "@graph": [
    {
      "@id": "eb:Card_003",
      "@type": "eb:Card",
      "rdfs:label": "Gaslighting",
      "rdfs:comment": "A manipulation tactic that makes someone question their perception of reality, memory, or emotions, in order to maintain power or avoid accountability.",
      "eb:colorZone": "red",
      "eb:intent": "control",
      "eb:patternType": "control tactic",
      "eb:exampleText": "You’re being way too sensitive. That’s not how it happened at all.",
      "eb:relationalImpact": "distorts reality",
      "eb:cardGroup": "Empathy Collapse"
    }
  ]
}

Why It Matters

Emotional harm is subtle—It hides in timing, tone, and intent disguised as care.

TEG-Code gives language to what usually goes unnamed.

This helps us track:

What real emotional safety vs. control feels like
How passive-aggressive “help” erodes trust
What actual repair looks and sounds like

It’s not just for AI.

It’s for therapy, design, education, parenting—any system holding humans.

Join the Development

We're seeking collaborators who understand that emotional intelligence isn't just "nice to have" - it's critical infrastructure for human-AI interaction.

For Researchers: Help validate the emotional logic against established literature and develop rigorous testing protocols.

For Clinicians:

Test cards against real client presentations and ensure the framework captures lived therapeutic experience.

For Developers: Implement TEG-Code in AI systems and measure outcomes - we need real-world performance data.

For Trauma Survivors: Ensure the framework accurately captures lived experience and doesn't replicate harmful clinical perspectives.

Especially seeking:

Neurodivergent researchers and coders
Trauma-informed AI safety teams
Clinical practitioners frustrated with current tools
Anyone who's felt the gap between emotional complexity and available language

If you recognize the problem TEG-Code solves, we want to hear from you.

If something in you says this matters—we want to hear from you.

AI Validation Through Direct Testing

Methodology: I tested TEG-Blue's concepts by directly prompting multiple AI systems (Claude, Copilot, Perplexity, DeepSearch) to analyze the framework's potential and identify gaps in current AI emotional intelligence.

What I did:

Presented the TEG-Blue framework to each AI system through chat interfaces
Asked them to evaluate whether current AI can distinguish trauma responses from manipulative behavior
Requested analysis of the framework's potential impact on AI safety
Gathered their assessments of what's missing in current emotional AI capabilities

Consistent AI Response: Every AI system confirmed they cannot currently distinguish between someone acting from trauma versus someone being manipulative - validating the core problem TEG-Blue addresses.

Key AI Assessment Quote: "Could revolutionize AI emotional intelligence by providing something current systems lack entirely: the ability to read emotional intent, not just emotional expression."

Research Insight Generated: Through this AI collaboration process, the projection emerged that "even a 70% accurate mode signal cuts toxic escalation by ≥30%."

What This Means: This represents direct validation from AI systems themselves that the gaps TEG-Blue addresses are real and significant. The AI systems became research partners in identifying their own limitations and confirming the framework's relevance.

Explore Next

What Is Emotional Technology — establishes the foundation of emotional tech

Bridging Human Emotional Intelligence & AI Safety — situates TEG-Code within AI ethics

EMLU — expands into multimodal emotional language understanding

Internal Links

TEG-Blue™ is a place for people who care-about dignity, about repair, about building something better. It’s a map, an invitation, and a growing toolbox, as an evolving commons—supporting emotional clarity, systemic healing, and collective wisdom. Here, healing doesn’t require perfection—just honesty, responsibility, and support.