Architecting Real-Time Moderation for Live Video

Live stream moderation involves two key paths to manage content: a fast, shallow path that blocks inappropriate content before it reaches viewers and a slower, deeper path that corrects decisions after the content has been seen. The effectiveness of these paths is determined by the delivery protocols like WebRTC and LL-HLS, which dictate the time available to moderate content before it is delivered to viewers. The fast path operates within this limited window, utilizing techniques like scoring fewer frames and compressing models to ensure quick decisions, often running these processes at the edge. In contrast, the slower path allows for thorough evaluations, possibly involving human oversight and more complex models, to retrospectively address any issues. For successful moderation, platforms need to measure precision, recall, and F1 scores by category and maintain an immutable log of decisions, important both for improving systems and for meeting regulatory requirements such as those set by the EU's Digital Services Act. The combination of these strategies allows for a balanced approach to managing the unique challenges of live stream content moderation.

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