Manage AI & Data Risk: Effective Strategies for Governing Information, Data & Artificial Intelligence
As artificial intelligence (AI) and data technologies evolve, organizations face an increasingly complex landscape of risks, regulations, and ethical concerns. "Manage AI & Data Risk: Effective Strategies for Governing Information, Data & Artificial Intelligence" serves as a comprehensive guide for leaders, professionals, and policymakers to navigate the challenges of AI systems while maintaining ethical and compliant data governance practices.
The book begins by demystifying the foundational elements of AI, from the basic components of machine learning and AI systems to the evolving AI technology stack. Readers are provided with a clear understanding of how AI has developed over time, alongside the corresponding evolution of data science.
Moving from technical foundations to the broader implications of AI, this guide explores the risks and harms posed by AI systems. Key principles of trustworthy AI are laid out, with comparisons between various ethical frameworks and guidelines that inform responsible AI use globally.
With an ever-changing regulatory environment, the book provides an in-depth analysis of how existing laws—like the EU's GDPR—interact with AI technologies. It covers liability reform and dives into the requirements of emerging AI laws, such as the EU AI Act and other global regulations. Readers will gain a detailed understanding of the major AI risk management frameworks, helping them to stay compliant with both current and future legal requirements.
The book also explores the AI life cycle in detail, breaking down the key phases of AI system planning, design, and implementation. This offers practical insights into how AI projects should be structured, tested, and validated for success.
Finally, the guide provides actionable strategies for implementing responsible AI governance and risk management. It outlines how organizations can ensure interoperability of AI risk management within their broader operational risk strategies and integrate AI governance principles into their corporate structure. Special focus is given to setting up AI governance infrastructure, planning and scoping AI projects, managing systems post-deployment, and understanding the legal, user, and auditing challenges that come with AI accountability.
Manage AI & Data Risk equips organizations with the knowledge they need to effectively govern AI and data systems while protecting against risks, ensuring compliance, and fostering trust with stakeholders. Whether you are a business leader, data scientist, risk manager, or policymaker, this book offers a practical roadmap for managing the future of AI and data responsibly.