
The Governance of Artificial Intelligence
- 1st Edition - April 1, 2026
- Latest edition
- Author: Tshilidzi Marwala
- Language: English
The Governance of Artificial Intelligence stands out as a comprehensive guide that unifies the essential dimensions of artificial intelligence—values, data, algorithms,… Read more

The Governance of Artificial Intelligence stands out as a comprehensive guide that unifies the essential dimensions of artificial intelligence—values, data, algorithms, computing, applications, and governance—within a single volume. The book offers expert guidance on each of these topics, blending engineering insight with governance strategies. It proposes a holistic approach to AI governance, emphasizing the importance of proactive and balanced policies that foster innovation while safeguarding ethical standards. Prioritizing social welfare and human rights, this work advocates for maximizing AI’s benefits and minimizing its risks through effective, integrative governance structures.
Moreover, the book highlights the need for a versatile governance model that draws from various disciplines and champions diversity. It stresses the importance of leveraging existing regulatory frameworks, ethical guidelines, and industry standards, while encouraging active collaboration among governments, businesses, civil society, and academia. Structured into six sections and 33 chapters, the book systematically explores core principles, data concerns, algorithms, computing, practical applications, and governance challenges, making it a crucial resource for understanding the evolving landscape of AI oversight.
Moreover, the book highlights the need for a versatile governance model that draws from various disciplines and champions diversity. It stresses the importance of leveraging existing regulatory frameworks, ethical guidelines, and industry standards, while encouraging active collaboration among governments, businesses, civil society, and academia. Structured into six sections and 33 chapters, the book systematically explores core principles, data concerns, algorithms, computing, practical applications, and governance challenges, making it a crucial resource for understanding the evolving landscape of AI oversight.
- Presents the critical issue of values in AI use, which is important given the proliferation of generative AI
- Demonstrates how to handle data and apply AI, including case studies for better understanding of the topics covered
- Deals with the complex problem of governing data, algorithms, computing, and applications to health, finance, and conflicts
- Includes a companion website with a series of videos from the author, providing supplementary information and guidance for understanding key concepts
Computer Science researchers, artificial intelligence researchers, and researchers and practitioners working in the field of IT management and public policy. The primary audience also includes data analysts, software engineers, as well as researchers and professionals across the fields of science and engineering
1. Introduction
SECTION A. AI Values
2. Risk Identification and Mitigation: Performance Risk Quantification
3. Transparency: Accuracy vs Transparency
4. Fairness: Avoidable and Unavoidable Algorithmic Bias and Discrimination
5. Truth: Algorithmic Deception
6. Inclusion
7. Balancing risks and opportunities: Pareto Optimality
SECTION B. Data Governance CHAPTER 8. Data Acquisition
9. Cross-Border Data Flow
10. Synthetic Data
11. Data Analysis
12. Data Storage
SECTION C. Algorithmic Governance
13. Algorithmic Selection
14. Algorithmic Design
15. Algorithmic Training
16. Algorithmic Testing
SECTION D. Computing Governance
17. Semiconductor Chips
18. Edge AI
19. Cloud Computing
20. Ambient Computing
21. Quantum Computing
22. Computing Energy
23. Computing Water
SECTION E. Applications
24. Finance
25. Health
26. Conflicts
SECTION F. AI Governance
27. Human Behavior
28. Mechanisms
29. Policy and Regulations
30. AI Standards
31. AI Laws
32. Conclusion
SECTION A. AI Values
2. Risk Identification and Mitigation: Performance Risk Quantification
3. Transparency: Accuracy vs Transparency
4. Fairness: Avoidable and Unavoidable Algorithmic Bias and Discrimination
5. Truth: Algorithmic Deception
6. Inclusion
7. Balancing risks and opportunities: Pareto Optimality
SECTION B. Data Governance CHAPTER 8. Data Acquisition
9. Cross-Border Data Flow
10. Synthetic Data
11. Data Analysis
12. Data Storage
SECTION C. Algorithmic Governance
13. Algorithmic Selection
14. Algorithmic Design
15. Algorithmic Training
16. Algorithmic Testing
SECTION D. Computing Governance
17. Semiconductor Chips
18. Edge AI
19. Cloud Computing
20. Ambient Computing
21. Quantum Computing
22. Computing Energy
23. Computing Water
SECTION E. Applications
24. Finance
25. Health
26. Conflicts
SECTION F. AI Governance
27. Human Behavior
28. Mechanisms
29. Policy and Regulations
30. AI Standards
31. AI Laws
32. Conclusion
- Edition: 1
- Latest edition
- Published: April 1, 2026
- Language: English
TM
Tshilidzi Marwala
Dr. Tshilidzi Marwala is the United Nations (UN) University Rector and UN Under-Secretary-General based in Tokyo, Japan. He was the Vice-Chancellor and Principal of the University of Johannesburg and a trustee of the Nelson Mandela Foundation. He is a member of the American Academy of Arts and Sciences, The World Academy of Sciences (TWAS) and the African Academy of Sciences. He has supervised 37 doctoral students from more than 20 countries in Africa, Asia, Europe, the Middle East, and the Americas. Dr. Marwala holds a Bachelor of Science in Mechanical Engineering (magna cum laude) from Case Western Reserve University, USA, and a Ph.D. in Artificial Intelligence from the University of Cambridge, UK. He has published 27 books on Artificial Intelligence, one translated into Chinese, over 500 articles in journals, proceedings, book chapters and newspapers, and he holds five international patents. He is the author of Hamiltonian Monte Carlo Methods in Machine Learning and Rational Machines and Artificial Intelligence from Elsevier/Academic Press.
Affiliations and expertise
Rector of the United Nations University and Under-Secretary-General of the United Nations, Tokyo, Japan