This book is the first practical book on AI risk assessment and management. It will enable you to evaluate and implement safe and accurate AI models and applications. The book features risk assessment frameworks, statistical metrics and code, a risk taxonomy curated from real-world case studies, and insights into AI regulation and policy, and is an essential tool for AI governance teams, AI auditors, AI ethicists, machine learning (ML) practitioners, Responsible AI practitioners, and computer science and data science students building safe and trustworthy AI systems across businesses, organizations, and universities.