DESCRIPTION
As AI systems become more agentic, their significance lies not only in autonomous task completion, but in how they enter wider loops of human judgment, tools, data, evidence, and social purpose. This panel explores how agentic AI can move from isolated assistants or autonomous tools toward shared capacity: the ability for people and communities to reason, create, test, and act with AI in more collective and accountable ways. Speakers will examine the interfaces, workflows, and harnesses that shape how agents are guided, interpreted, evaluated, and connected to real-world problems. The discussion may include agentic AI for research, knowledge synthesis, policy exploration, public-interest technology, simulation, multilingual collaboration, and other settings where human and machine capabilities are combined. The panel asks how AI Agents can be made useful, legible, and adaptable in support of public value and inclusive futures.
