Brand Safety

Brand safety focuses on protecting brands from reputational damage by identifying and mitigating harmful content, extending beyond simple toxicity detection to encompass a broader range of potentially damaging contexts for advertising. Current research emphasizes developing robust automated systems for content moderation, often employing machine learning techniques like binary classification and reinforcement learning (particularly dual-agent approaches for risk-aware policy learning) to analyze user-generated content and assess risk. These advancements are crucial for improving online safety and enabling responsible advertising practices across various platforms, impacting both the effectiveness of online marketing and the overall user experience.