ModelRefs / Toxicity Detection — AI Glossary
Toxicity Detection — AI Glossary
Automated measurement of the degree of offensive, harmful, or abusive language in model outputs.
Overview
Toxicity detection models (Perspective API, HateBERT, Detoxify) score text on dimensions: toxicity, severe toxicity, obscenity, threat, insult, identity attack. Used in RLHF feedback loops (penalizing toxic completions), production output monitoring, and benchmark datasets. Perspective API (Google Jigsaw) is the most widely used baseline.
Reference details
| Topic | safety |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Toxicity Detection — AI Glossary.
Frequently asked questions
What is Toxicity Detection?
Automated measurement of the degree of offensive, harmful, or abusive language in model outputs.
What concepts are related to Toxicity Detection?
Closely related concepts include content moderation, bias detection, guardrails.