Safety Specification

Safety specification research focuses on ensuring the safe operation of autonomous systems and AI models, primarily by preventing harmful or unintended behaviors. Current efforts concentrate on developing robust safety mechanisms, including control barrier functions for robotic systems, Bayesian optimization techniques for time-varying environments, and shielding methods that correct unsafe actions in reinforcement learning and large language models. These advancements are crucial for deploying AI in safety-critical applications like autonomous driving and robotics, improving reliability and trustworthiness.