AI Risk Management, Analysis, and Assessment.
By Anand Vemula
Length2h 22m
About this audiobook
This book provides a comprehensive exploration of AI risk management, addressing foundational concepts, advanced analysis methodologies, assessment frameworks, governance models, industry-specific applications, and future challenges. Beginning with the fundamentals, it clarifies key definitions and classifications of AI risks, differentiates risk from uncertainty, and examines historical lessons. It categorizes risks across technical, ethical, economic, and environmental dimensions, emphasizing the evolving lifecycle of AI risk from design through deployment and continuous monitoring.
The discussion advances into rigorous risk analysis techniques, combining quantitative and qualitative approaches such as probabilistic risk assessment, scenario simulation, and bias audits. AI-specific modeling techniques including causal networks, Monte Carlo simulations, and agent-based models are explored, highlighting tools to detect and mitigate bias and fairness issues while improving explainability.
Frameworks and standards like NIST AI RMF, ISO/IEC guidelines, and OECD principles provide structured approaches to risk assessment, while operational practices and toolkits integrate risk considerations directly into AI development pipelines.
Governance sections detail internal structures, accountability mechanisms, and legal challenges including cross-border compliance, data protection, and liability. Third-party and supply chain risks emphasize the complexity of AI ecosystems.
Industry-focused chapters explore sector-specific risks in healthcare, finance, and defense, illustrating practical applications and regulatory requirements.
Audiobook details
GenreEducation and Learning, Self-Help
Length2 hrs 22 mins
Narrated byListen with 1,000+ voices
FormateBook with Audio
Publish dateMay 30, 2025
LanguageEnglish
Table of contents
11. Understanding AI Risk
22. Types of Risks in AI
33. Risk Lifecycle in AI Systems
44. Quantitative and Qualitative AI Risk Analysis
55. AI Risk Modeling Techniques
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66. Bias, Fairness, and Explainability Audits
77. Risk Assessment Standards and Guidelines
88. Operationalizing Risk Assessment
99. Toolkits and Platforms for Risk Assessment
1010. AI Governance Models
1111. Legal and Regulatory Risk
1212. Third-party and Supply Chain Risk
1313. Healthcare and Medical AI Risks
1414. Financial and Insurance Sector Risks
1515. Public Sector and Defense
1616. Emerging AI Risks
1717. AI Risk in the Age of AGI
1818. Toward Resilient and Trustworthy AI
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