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The Governance of Artificial Intelligence provides an essential approach to AI governance, including proactive and comprehensive strategies that efficiently balance innovation and ethical concerns. The book prioritizes social welfare and upholds human rights by maximizing the benefits of AI while reducing its negative aspects. Sections address the principles that govern artificial intelligence, data-related topics, AI algorithms, the issue of computing, applications, and AI governance. Throughout each section, the idea that it is essential to implement a versatile governance structure that incorporates several fields of study and encourages diversity is reinforced. Additionally, utilizing existing regulatory frameworks, ethical standards, and industry benchmarks is essential.
Moreover, the book maintains that it is crucial to integrate cooperation between governments, economic organizations, civil society, and the academic community under a multi-stakeholder framework to promote transparency, accountability, and public trust in AI systems. Because of the fast pace of technological progress, the opaqueness of AI algorithms, worries about bias and impartiality, the requirement for accountability in AI-based decisions, and the global nature of AI development and deployment, it is imperative to cultivate global cooperation in regulating AI as its impacts extend beyond national boundaries. AI governance involves establishing worldwide norms and standards that encourage coordinating governance efforts while recognizing cultural and geographical differences.
List of contents
1. Introduction
SECTION A. AI Values2. 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 Acquisition9. Cross-Border Data Flow
10. Synthetic Data
11. Data Analysis
12. Data Storage
SECTION C. Algorithmic Governance13. Algorithmic Selection
14. Algorithmic Design
15. Algorithmic Training
16. Algorithmic Testing
SECTION D. Computing Governance17. Semiconductor Chips
18. Edge AI
19. Cloud Computing
20. Ambient Computing
21. Quantum Computing
22. Computing Energy
23. Computing Water
SECTION E. Applications24. Finance
25. Health
26. Conflicts
SECTION F. AI Governance27. Human Behavior
28. Mechanisms
29. Policy and Regulations
30. AI Standards
31. AI Laws
32. Conclusion
About the author
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.
