Legal Autonomy

Legal autonomy in artificial intelligence focuses on enabling AI agents to operate lawfully and responsibly, primarily by either constraining AI actors or limiting AI's environmental impact. Current research emphasizes developing frameworks for autonomous systems across diverse applications (e.g., robotics, autonomous vehicles, mental health support), often employing machine learning models like Bayesian networks, deep reinforcement learning, and large language models (LLMs) to achieve adaptable and explainable behavior. This research is crucial for ensuring the safe and ethical deployment of increasingly autonomous systems, impacting fields ranging from manufacturing and transportation to healthcare and space exploration.