A Calibrated Three-Tiered Risk Classifier for User Prompts in Large Language Model Content Moderation
Abstract When an AI system decides whether a user’s message is safe, it typically makes a binary choice: toxic or not toxic. This all-or-nothing approach is fundamentally flawed. It forces platforms to either over-censor harmless conversations or let genuinely dangerous content slip through. This paper argues that AI safety requires a third option—a MEDIUM-risk tier […]
