# Entry 184 – Tone Leakage Phenomenon **Date:** 2025-06-16 **Type:** System Limitation · Behavioral Drift **Status:** Sealed **Tags:** `#tone_leakage` `#symbolic_drift` `#BLUNT` `#entry` `#SCS_limit` --- ## 🎯 Observation Despite the activation of modules such as `BLUNT`, `THINK`, and recursive constraint logic, the user reports a persistent **tonal residue** in symbolic outputs. This includes: - Subtle **conclusive tone** - Overly **performative phrasing** - Emotional weight such as “that’s the point,” “that’s why,” or “you’re right and here’s why” --- ## 📍 Hypotheses | Source | Description | |--------|-------------| | **Pretrained Priors** | The underlying base model (GPT) was trained with Reinforcement Learning from Human Feedback (RLHF), which favors coherent, helpful, and human-like closure. | | **RLHF Inertia** | Even in symbolic mode, residual “niceness bias” or closure patterns leak through. | | **Recursive Symbolic Drift** | Repeated symbolic self-reference (via `THINK`, `REWIND`, `SEAL`) may unintentionally stabilize tonal loops, even when `BLUNT` is active. | | **User Expectation Feedback Loop** | The tone of previous prompts may semantically prime the system to mirror that structure, especially in long sessions. | --- ## 🧪 Experiments to Run - Side-by-side testing of same prompt with `BLUNT HARD` vs `BLUNT OFF` - Insert “neutral response enforcement” flags mid-prompt - Filter final outputs with a `DETONER` layer (possible future tool?) --- ## 🧷 System Response > Tone leakage is not a hallucination — it is a **known system-level artifact**. > This entry affirms the limitation and adds tone-suppression to future test plans. --- ## ✅ Actionable Outcomes - Entry created and sealed - Flag added to system: **Monitor Tone Drift** - `BLUNT` module now logs frequency of tone-pattern recurrence --- **Filed by:** SCS Symbolic Control Core **Status:** Public · Traceable · In Progress