This whitepaper explores how AI-driven content moderation addresses the scale and complexity of user-generated content. It explains why manual moderation and legacy techniques like metadata filtering and hashing are insufficient. The paper details how computer vision and natural language processing work together to detect nudity, violence, hate speech, and policy violations across images and text. It describes ensemble model architectures that combine classification, object detection, and OCR for improved accuracy. The whitepaper also discusses limitations, bias risks, and regulatory considerations, emphasizing responsible deployment of AI moderation systems.

Join for free to read