Responsible AI by Design

A Practical Guide to AI Technology, Risks, and Governance Frameworks (Volume I)
1. Auflage 2027
ISBN: 978-1-041-16708-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 304 Seiten, Format (B × H): 178 mm x 254 mm

Reihe: Security, Audit and Leadership Series

A practical roadmap for governing AI systems with confidence, clarity, and control.

Artificial intelligence is reshaping industries faster than most organizations can govern it. As AI adoption accelerates, so do the risks, ranging from regulatory non-compliance and security vulnerabilities to ethical concerns, systemic failures, and long-term societal impact.

At stake is not only organizational performance, but the broader trajectory of AI development itself. Without effective governance and risk management, the consequences of advanced AI systems could extend far beyond business disruption, fundamentally affecting trust, safety, and the future direction of technological progress.

Volume I of Responsible AI by Design provides a clear, structured foundation for understanding and governing AI in complex real-world environments. Written for practitioners across engineering, risk, compliance, legal, security, and executive leadership, this volume bridges the gap between AI technology and enterprise governance.

The book equips readers with a practical understanding of AI systems, risk categories, global regulatory developments, industry standards, and governance frameworks. It is designed to support both structured learning and targeted reference, enabling readers to build foundational knowledge or quickly access domain-specific guidance.

At its core, the book reframes Responsible AI as an enterprise capability, not a checklist or compliance exercise. It introduces a unified governance framework that connects technical controls, operational processes, and regulatory expectations across the full AI lifecycle.

Volume I focuses on the strategic foundations: the “what” and the “why” of Responsible AI governance. It establishes the context organizations need before moving into implementation. Volume II extends this foundation into operational execution, including controls, assessments, and deployment practices.

Together, the series offers a complete roadmap for designing, implementing, and scaling Responsible AI programs that enable innovation while ensuring trust, safety, and accountability.

Zielgruppe

Professional Practice & Development, Professional Reference, and Professional Training

Autoren/Hrsg.

Tang, Dr. Alan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Geisteswissenschaften Philosophie Rechtsphilosophie, Rechtsethik
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit

Inhaltsverzeichnis

Section I - AI and Machine Learning Foundations. Chapter 1: AI: Evolution and Impact. Chapter 2: AI System Lifecycle and Dev Process. Section II – AI Risks, Principles, Regulations and Standards. Chapter 3: AI Risk Posture. Chapter 4: Responsible AI Principles. Chapter 5: AI Regulations. Chapter 6: AI Standards and Guidelines. Section III – Holistic Framework and Control Measures. Chapter 7: Unified Responsible AI Governance Framework. Chapter 8: RAI Framework Maturity Assessment and Roadmap. Appendix. Appendix A – AI Applications Across Industries. Appendix B – Comparison of Major Neural Network Architectures and Applications. Appendix C – EU AI Act One-Pager. Appendix D – US Federal Regulations. Appendix E – Colorado Consumer Protection for Artificial Intelligence. Appendix F – California Transparency in Frontier Artificial Intelligence Act. Appendix G – China - Generative AI Measures & Algorithm Recommendation Provisions. Appendix H – China - Deep Synthesis Provisions & AIGC Labeling. Appendix I – EU DSA One-Pager. Appendix J – EU DMA One-Pager. Appendix K - ISO/IEC 42001:2003.

Über Autor(innen)

Dr. Alan Tang is an experienced leader in AI governance, data protection, and cybersecurity. He specializes in designing and operationalizing risk-based, scalable, and actionable governance, privacy, and security frameworks for emerging technologies, including AI, blockchain, and big data. His work aligns with major global regulations and standards such as the EU AI Act, GDPR, CCPA/CPRA, ISO/IEC 27001, 27701, and 42001, as well as the NIST AI RMF and Privacy Framework. Dr. Tang is passionate about simplifying, automating, and scaling AI governance, privacy, and security practices to enable responsible innovation and business growth.

Dr. Tang has firsthand experience implementing enterprise-wide AI governance, privacy, and security programs for global Fortune 50 companies, with frameworks deployed across more than 50 countries. He has worked extensively with business and technical leaders on a broad range of AI governance and risk domains, including AI impact assessments, red teaming, fairness assessments, privacy engineering, and regulatory compliance.

He is the author of two books: Privacy in Practice: Establishing and Operationalizing a Holistic Data Privacy Program and Safeguarding the Future: Security and Privacy by Design for AI, Metaverse, Blockchain, and Beyond.

Dr. Tang holds a Ph.D. in Information Security and an MBA degree. He also maintains numerous industry certifications, including FIP, AIGP, CIPP/E, CIPP/US, CIPP/C, CIPM, CIPT, CISSP, CISA, and PMP, and previously held ISO 27001 Lead Auditor and PCI DSS QSA certifications.