Lilly Tech Systems
Beginner
AI-Powered Content Moderation
AI moderation processes thousands of posts per minute, catching spam, hate speech, misinformation, and policy violations that would overwhelm human moderators — keeping communities safe and welcoming at any scale.
Moderation Categories
| Category | AI Detection Method | Action |
|---|---|---|
| Spam | Pattern recognition, link analysis, account behavior | Auto-remove, flag for review |
| Toxicity | NLP sentiment and hate speech classifiers | Auto-hide, warn user, escalate |
| Misinformation | Fact-checking APIs, source credibility scoring | Label, reduce distribution, link to facts |
| NSFW Content | Computer vision image/video classification | Auto-remove, ban repeat offenders |
| Self-Harm | Specialized NLP models for crisis language | Immediate alert, provide resources |
Key Insight: The best moderation systems use a tiered approach: AI handles clear-cut violations (spam, obvious hate speech) automatically, flags borderline content for human review, and learns from human decisions to improve over time.
Moderation Tools
Perspective API
Google's free API that scores text for toxicity, insults, threats, and profanity with customizable thresholds.
Community.ai
AI moderation built for community platforms with custom rule sets, member reputation scoring, and appeals management.
Hive Moderation
Visual content moderation using computer vision for NSFW detection, violence, and brand safety in images and video.
OpenAI Moderation
Free moderation endpoint that classifies text across multiple categories including violence, self-harm, and sexual content.
Building Fair Moderation Systems
- Bias Testing: Regularly audit AI moderation for demographic bias and disproportionate enforcement
- Appeals Process: Provide clear, accessible appeals for users whose content is moderated incorrectly
- Transparency: Publish community guidelines and explain how AI moderation works
- Continuous Training: Feed human moderation decisions back into AI models for ongoing improvement