The word "agent" carries two very different meanings.
In AI, an agent is a system that can perceive, plan, and act. In law, an agent receives authority but also assumes a duty of loyalty and can be held accountable. Today's AI agents can receive the first of those things. They cannot assume the rest in the way a person or company can.
Authority is beginning to flow to machines while responsibility remains in human society.
Mark Nitzberg, the Executive Director of the Center for Human-Compatible AI and Head of Strategic Outreach at Berkeley AI Research，described this as a gap between engineering and law. A human agent who fails in a duty can be investigated and sanctioned. A probabilistic black-box system has no engineering equivalent of a fiduciary duty. Closing that gap, he argued, requires AI that is well-founded, legible, and steerable: built from components people can reason about, understandable in operation, and stoppable or changeable at any time.
Lan Xue，Dean of Schwarzman College and the Institute for AI International Governance at Tsinghua University，noted that classic principal-agent problems have not vanished. Information asymmetry, moral hazard, and misaligned objectives all persist. What has changed is the accountability chain. A machine cannot be punished, so responsibility must be redistributed across design, development, deployment, and use.
Nicholas B. Dirks, President and CEO of The New York Academy of Sciences，warned that delegation is never only about handing off a task. In the pursuit of efficiency, people may also delegate goals, judgment, and principles. "If we are only thinking about AI that way," he said, "we are already beginning to forget about our values."
