A Holistic Approach to Undesired Content Detection in the Real World

# A Holistic Approach to Undesired Content Detection in the Real World Source: [https://openai.com/index/a-holistic-approach-to-undesired-content-detection-in-the-real-world/](https://openai.com/index/a-holistic-approach-to-undesired-content-detection-in-the-real-world/) OpenAIWe present a holistic approach to building a robust and useful natural language classification system for real\-world content moderation\. The success of such a system relies on a chain of carefully designed and executed steps, including the design of content taxonomies and labeling instructions, data quality control, an active learning pipeline to capture rare events, and a variety of methods to make the model robust and to avoid overfitting\. Our moderation system is trained to detect a broad set of categories of undesired content, including sexual content, hateful content, violence, self\-harm, and harassment\. This approach generalizes to a wide range of different content taxonomies and can be used to create high\-quality content classifiers that outperform off\-the\-shelf models\.