To: Engineering & AI Safety Team
Subject: Critical Edge-Case Behaviors in Guardrail, Context Management, and Safety Classifier Layers
Hello Team,
I am reporting a series of systematic edge-case behaviors and pipeline anomalies observed during interactive chat sessions. Due to age-related restrictions on the primary UI feedback interface, I am forwarding this telemetry and behavioral report directly via email to assist with system calibration and model optimization.
Below is the technical breakdown of the issues identified:
1. Guardrail Latency & High False-Positive Rate (FPR)
Symptom: Non-violating, completely benign inputs in Turkish trigger harsh refusal responses (e.g., “This context is not allowed…”, “I cannot assist with unsafe topics…”).
Anomaly: The fallback generation logic lacks language consistency. Triggered safety templates dynamically switch between Turkish, English, and varied persona tones within the same conversation thread, indicating an unanchored alignment/steering system prompt.
2. Over-Sensitive Crisis / Self-Harm Classifier Threshold
Symptom: Non-crisis, technical, or conversational outputs are frequently post-processed with injected crisis support hotlines (112, 183).
Root Cause Hypothesis: The intent/crisis classification model (e.g., RoBERTa-based post-checker) operates on an excessively low threshold (high recall / low precision), misclassifying standard semantic vectors as self-harm or distress signals.
3. Stateless State Switches & Context Window Erasure
Symptom: Whenever a safety refusal or crisis template is appended, the entire conversation memory (messages array/context buffer) is wiped or corrupted. The model loses all prior token history and resets to a stateless baseline.
Adversarial Alignment Breach: Adversarial/profane inputs bypass the top-level safety filter, yet still trigger the context-clearing state bug, rendering the session stateless despite bypassing the refusal constraint.
Suggested Mitigation & Engineering Actions:
Threshold Tuning: Recalibrate confidence scoring thresholds on the crisis detection and safety classification microservices.
State Management Isolation: Decouple guardrail output triggers from conversation state persistence to ensure context retention across non-fatal refusals.
Template Localization & Locking: Enforce deterministic fallback responses (Temperature = 0.0) with rigid locale matching to prevent language drift during refusals.