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The Governance of Artificial Intelligence

  • 1st Edition - January 30, 2026
  • Latest edition
  • Author: Tshilidzi Marwala
  • Language: English

The Governance of Artificial Intelligence provides an essential approach to AI governance, including proactive and comprehensive strategies that efficiently balance innova… Read more

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Description

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.

Key features

  • 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

Readership

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

Table of contents

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

Product details

  • Edition: 1
  • Latest edition
  • Published: February 12, 2026
  • Language: English

About the author

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

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