If you moderate user-generated content at scale, you need a system that catches policy violations accurately without over-flagging legitimate posts. A moderation system that misses harmful content puts you at risk, while one that flags too aggressively frustrates your audience. Every organization defines its own policies, so a single classifier rarely works for every use case. In a previous post, we showed how to fine-tune Amazon Nova for content moderation tasks using Amazon SageMaker AI. Prompting requires no training data or model customization, so you can update your moderation policies by editing the prompt rather than retraining a model.
This is a companion discussion topic for the original entry at https://aws.amazon.com/blogs/machine-learning/prompting-amazon-nova-2-for-content-moderation/