Achieving Safe and Compliant Generative AI: Lessons from Model Risk Management

Generative AI has sparked widespread discussions regarding its safety and ethical implications, and it is crucial to navigate this rapidly evolving landscape with a responsible and well-informed approach. In this webinar, join Ramesh Dontha and special guests Dr. Jon Hill, Professor of Model Risk at NYU Tandon School of Financial Risk Engineering, David Van Bruwaene, Co-Founder and CEO at Fairly AI, and Hassan Patel, Director of Global AI Policy Compliance Engineering at Fairly AI as they explore the fascinating intersection between Generative AI and Model Risk Management (MRM) best practices. Drawing upon Dr. Hill's extensive expertise in MRM, David's academic background in ethics and industry experience in leading AI startups as well as Hassan's policy expertise and involvement in developing ethical AI standards, we will uncover valuable lessons that can be applied to the development and deployment of generative AI models. By examining the rigorous processes and controls employed by banks to manage risks associated with financial models, we can gain insights into establishing responsible and ethical practices for generative AI. Did you know? The U.S. NIST AI Risk Management Framework was drawn upon the Model Risk Management framework from the banking industry? Join us as we discuss: - Understanding the core principles of Model Risk Management and their relevance to generative AI - Discussing the intersection of regulation, ethics, and technological innovation in the context of generative AI - Leveraging lessons from MRM frameworks to establish robust governance and accountability in generative AI By attending this webinar, you will gain a unique perspective on the ethical generative AI debate, combining the expertise of ethics, AI, model risk management and policy, and much more. Reserve your spot now!