Safety Risk

Safety risk in artificial intelligence, particularly concerning large language models (LLMs) and autonomous vehicles, is a critical research area focused on identifying and mitigating vulnerabilities that lead to unsafe outputs or behaviors. Current research emphasizes developing robust evaluation methods and datasets, such as multi-task safety moderation datasets, to benchmark model performance and identify weaknesses across various risk categories, including malicious intent detection and harmful content generation. These efforts aim to improve the safety and reliability of AI systems through the development of improved moderation tools and safety-enhancing algorithms, ultimately impacting the responsible deployment of AI in real-world applications.