Abstract for: Agentic AI for Dynamic Modeling and Governance in SocioTechnical Systems

Agentic AI offers transformative potential for dynamic modeling and governance in complex sociotechnical systems. This talk explores how sophisticated AI agents, capable of modeling realistic human decision-making, bounded rationality, and strategic behavior, significantly improve our ability to represent complex interactions within dynamic social environments. By capturing nuanced human-like decision processes, these AI agents allow researchers and policymakers to better understand emergent behaviors and system responses in real-time. The flexibility and sophistication of these agents provide a powerful framework for designing adaptive governance interventions and dynamic policies, enhancing responsiveness to evolving conditions. Through applications ranging from electric vehicle policy to strategic network interventions in social dilemmas, I demonstrate how Agentic AI enables experimentation with targeted, real-time interventions that can steer complex systems towards desirable outcomes. Ultimately, integrating Agentic AI into sociotechnical modeling not only enriches our analytical capabilities but also offers innovative, practical solutions to complex governance challenges. Ultimately, integrating Agentic AI into sociotechnical modeling not only enriches our analytical capabilities but also offers innovative, practical solutions to complex governance challenges. in modeling