Author Description

Artificial Intelligence (AI) is revolutionizing industries, yet its rapid evolution presents unprecedented challenges in governance, ethics, and security. Auditing Artificial Intelligence is an essential guide for IT auditors, information security experts, and risk management professionals seeking to understand, evaluate, and mitigate AI‑related risks. This book provides a structured framework for auditing AI systems, covering critical areas such as governance, compliance, algorithm transparency, ethical accountability, and system performance. With 24 insightful chapters, it explores topics including: AI Governance and Ethics – Establishing frameworks to ensure fairness, accountability, and transparency in AI deployments. Risk Management and Compliance – Addressing the legal and regulatory landscape, including GDPR, the EU AI Act, and ISO standards. Bias and Trustworthiness – Evaluating AI decision‑making to detect bias and ensure equitable outcomes. Security and Continuous Monitoring – Safeguarding AI systems from adversarial attacks and ensuring operational consistency. Model Performance and Explainability – Assessing AI outputs, refining accuracy, and ensuring alignment with business objectives. Designed for professionals tasked with assessing AI systems, this book combines practical methodologies, industry standards, and real‑world audit questions to help organizations build responsible and resilient AI practices and assess associated risks. Whether you are assessing AI governance, monitoring AI‑driven risks, or ensuring compliance with emerging regulations, this handbook provides the guidance you need to navigate and assess the complexities of AI systems with confidence. Stay ahead in your role and responsibility for assessing the rapidly evolving deployment and use of AI across the organization – equip yourself with the knowledge and tools to ensure its responsible, safe, approved, secure, and ethical use.