The Governance of Artificial Intelligence

Erscheinungsjahr 2026
ISBN: 978-0-443-36322-1
Verlag: Elsevier Science

Buch, Englisch, 250 Seiten, Format (B × H): 216 mm x 276 mm, Gewicht: 450 g

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.

Autoren/Hrsg.

Marwala, Tshilidzi

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Sozialwissenschaften Politikwissenschaft Internationale Beziehungen
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
• Mathematik | Informatik EDV | Informatik Informatik Natürliche Sprachen & Maschinelle Übersetzung
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung

Inhaltsverzeichnis

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

Über Autor(innen)

Marwala, Tshilidzi
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.