How would you remove toxic content from a web-scale pre...

Removing toxic content at scale is best achieved by training specialized fastText classifiers on the Jigsaw dataset. It is standard practice to train separate models for different categories of toxicity, such as hate speech and NSFW content. When deploying these, engineers must balance the precision-recall trade-off to ensure toxic content is removed without creating excessive false positives. Rule-based blocklists are generally insufficient as they are easily bypassed and fail to handle the complexity of natural language.