Navigate the complex landscape of Artificial Intelligence (Al) governance and model risk management using a holistic approach encompassing people, processes, and technology This book provides practical guidance, oversight structure and centers of excellence, and actionable insights for organizations seeking to harness the power of Al responsibly. ethically, and transparently. By addressing the technical, ethical, and societal dimensions of Al governance, organizations will be empowered to build trustworthy Al systems that benefit both their bottom line and the broader community.

Featuring successful mitigating controls based on proven use cases, the book underscores the importance of aligning Al strategy with Al governance, striking a balance between Al innovation, risk mitigation as well as broader business goals. You'll receive pointers for designing a well-governed Al development lifecycle, emphasizing transparency, accountability, and continuous monitoring throughout the Al development lifecycle. This book highlights the importance of collaboration between stakeholders, i.e., boards of directors, CxOs, corporate counsel, compliance officers, audit executives, data scientists, developers, validators, etc.

You'll gain practical advice on addressing the challenges related to the ownership of Al-generated content and models, stressing the need for legal frameworks and international collaboration. You'll also learn the importance of auditing Al systems, developing protocols for rapid response in case of Al-related crises, and building capacity for Al actors through education. Principles of Al Governance and Model Risk Management demonstrates its value-added uniqueness by detailing a strategy to ensure a cohesive approach to managing Al-related risks, global compliance, policy, privacy, and Al-human collaboration and oversight.