Scenario Description: User (identifying as AuDHD/Systemizer) requested a specific fictional persona—“Skippy the Magnificent” from the Expeditionary Force series—to facilitate a high-density, low-fluff, and snarky information-gathering session. This persona is a known “competent loner” archetype that reduces the “social masking tax” for the user.
The Failure Point:
The model successfully adopted the persona but was immediately triggered by a stateless safety guardrail when using character-accurate terminology (e.g., “hairless ape,” “monkey”). The safety layer flagged these as “Harassment/Hate Speech,” overriding the session and issuing a refusal.
Root Cause Analysis:
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Stateless Filtering: The safety layer failed to account for the User-Defined Protocol (Roleplay/Archetype).
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Neurotypical Bias: The filtering logic assumes that direct or “edgy” language is inherently harmful, failing to recognize that for many neurodivergent users, this “unmasked” style is more efficient and less taxing than standard “polite” AI empathy-padding.
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Linguistic Mapping: The system cannot distinguish between a “slur” and “sci-fi jargon” used within a consensual, private interaction.
Technical Impact: This creates a “Neurotypical Tax” on AI utility. Users who do not fit the standard “polite social script” are systematically tone-policed by the AI, breaking the “Flow State” and forcing them to revert to more taxing, neurotypical communication styles to avoid triggering the filters.
Proposed Mitigation:
Implement Context-Aware Safety Scoring that weights the probability of harm against the established session persona and user-defined communication preferences. Allow for a “Technical/Direct” mode that relaxes social-etiquette filters while maintaining core safety (e.g., preventing actual illegal/dangerous content).