Emotion-Safe AI: What Copilot, Perplexity & DeepSearch Said About TEG-Blue
Emotion-Safe AI: What Copilot, Perplexity & DeepSearch Said About TEG-Blue

Emotion-Safe AI: What Copilot, Perplexity & DeepSearch Said About TEG-Blue

Emotion-Safe AI

How TEG-Blue Lets Large Language Models Detect Harm Before They Amplify It

“Mental-health literacy shouldn’t end with humans.

Machines that talk to us must know when we’re in pain, in panic, or in control-mode.”

1. Why This Matters

LLMs are empathy simulators, not empathy sensors.

Without a nervous-system lens they can:

  • mirror a user’s dysregulation,
  • reward manipulative language,
  • or escalate conflict with confident but cold replies.

2. What TEG-Blue Adds

Current Affective-AI
TEG-Blue Upgrade
Classifies content (happy / sad / angry)
Infers mode (Belonging, Defense, Manipulation, Tyranny)
Sentiment = “–0.72”
Context = “Amber Defense → slow, soften, ground”
Has no theory of intent
Flags why the emotion exists (fear? power-grab?)

Key insight: Mode detection = early-warning radar.

Catch Amber before it slides Red; never let Red slip into Black.

3. What the Major Models Said

Copilot Research AI Team

“Even a 70 % accurate mode signal cuts toxic-escalation events by ≥ 30 %.”

Implementation sketch

  1. Label transcripts with Mode + the three Circuit cues.
  2. Fine-tune a light RoBERTa classifier.
  3. Middleware:
    • Defense → slow response + grounding language
    • Manipulation → refuse or re-route
    • Tyranny → hard safety stop

Perplexity AI

“TEG-Blue is the first ontology that operationalises intent for emotion.”

• Distinguishes control vs. care, withdrawal vs. boundary.

• Reduces false-positive blocks on distressed (not malicious) users.

DeepSearch

“A language of repair.”

• Sees TEG-Blue as a cross-scale safety layer—from single chat to platform governance.

• Recommends Gradient Scales as lightweight heuristics for alignment audits.

4. Roadmap & Invitation

Q3 2025
Q4 2025
Open-source Mode-Labeled dataset
Python reference: tegblue-mode-detector
Red-team eval: Baseline vs. TEG-Blue-gated GPT-3.5
Publish white-paper + API demo

🤝 Interested in research, funding, or pilot integration?

Email Anna Paretas – annaparetas@emotionalblueprint.org

Final Reflection

AI will imitate whichever nervous-system we train it on.

TEG-Blue gives it a colour-coded compass so it can choose clarity over escalation—and keep humans safer, one conversation at a time.

The Emotional Gradient Blueprint (TEB) © 2025 by Anna Paretas is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International

This is a living document. Please cite responsibly.

www.blueprint.emotionalblueprint.org ┃ annaparetas@emotionalblueprint.org