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Implementing AI Content Moderation: Lessons from Production

JM
Jake Morrison
|2024-10-30|7 min read
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AI-generated content needs moderation. User inputs that reach AI need moderation. The outputs that go to users need moderation. Here's how to build moderation that works without destroying user experience.

Layer your moderation. Fast, cheap filters catch obvious problems (profanity, known bad patterns). Slower, more sophisticated AI moderation handles nuanced issues. Human review handles edge cases and appeals. Each layer is optimized for its role.

False positives hurt more than you'd expect. Block legitimate content too aggressively and users lose trust, seek workarounds, or leave. Tune thresholds based on your specific risk tolerance.

Context matters for moderation decisions. "Kill" is fine in gaming contexts, problematic in others. Medical discussions include anatomical terms that trigger naive filters. Build context-aware moderation or accept that generic solutions will have gaps.

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JM

Jake Morrison

Contributing writer at MoltBotSupport, covering AI productivity, automation, and the future of work.

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