The Governance of Artificial Intelligence

Nyhet

Häftad, Engelska, 2026

2 229 kr

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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.

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

Produktinformation

Utgivningsdatum2026-04-01
Mått216 x 276 x undefined mm
Vikt450 g
FormatHäftad
SpråkEngelska
Antal sidor250
FörlagElsevier Science
ISBN9780443363221

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Internationella relationer inom Samhalle och politik
Företagsekonomi inom Ekonomi och ledarskap
Affärsapplikationer inom Data och it
Artificiell intelligens inom Data och it
Systemvetenskap och AI inom Data och it

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.

1. IntroductionSECTION A. AI Values2. Risk Identification and Mitigation: Performance Risk Quantification3. Transparency: Accuracy vs Transparency4. Fairness: Avoidable and Unavoidable Algorithmic Bias and Discrimination5. Truth: Algorithmic Deception6. Inclusion7. Balancing risks and opportunities: Pareto OptimalitySECTION B. Data Governance CHAPTER 8. Data Acquisition9. Cross-Border Data Flow10. Synthetic Data11. Data Analysis12. Data StorageSECTION C. Algorithmic Governance13. Algorithmic Selection14. Algorithmic Design15. Algorithmic Training16. Algorithmic TestingSECTION D. Computing Governance17. Semiconductor Chips18. Edge AI19. Cloud Computing20. Ambient Computing21. Quantum Computing22. Computing Energy23. Computing WaterSECTION E. Applications24. Finance25. Health26. ConflictsSECTION F. AI Governance27. Human Behavior28. Mechanisms29. Policy and Regulations30. AI Standards31. AI Laws32. Conclusion