Artificial Intelligence and Safety

In a world where machines learn, evolve, and sometimes outthink us, Artificial Intelligence and Safety offers a rare, integrated lens into both the power and peril of intelligent systems. Drawing on the authors' unique blend of programming mastery and enterprise risk leadership, this guide is your compass in the age of intelligent machines. This book goes beyond traditional risk management frameworks by integrating the latest advancements in artificial intelligence (AI) and generative AI. Combining real-world case studies, Socratic questioning, and the wisdom of AI governance pioneers, it journeys through the evolution of AI, the rise of deep learning, and the practical implications of large language models (LLMs) and retrievalaugmented generation (RAG). The authors translate complex technical knowledge into actionable insights and teach how to use Python not just for prediction, but for protection-turning code into a risk management ally. Readers will understand how to embed ethics by design, assess emerging risks, and confidently apply AI governance frameworks. This guide demystifies AI for everyone-from software architects to policymakers and risk managers. Whether you're crafting LLMs or setting enterprise policy, this book empowers you to not only ask the right questions but build the right systems, because the future of AI isn't just about building intelligence, it's about building it responsibly.

Charu Khanna is director of risk management at a global financial institution. She has extensive experience in risk management, data and operational risk, and analytics. Sahil Khanna is a senior data scientist and AI governance specialist with extensive experience in designing and deploying machine learning and LLM solutions across healthcare, retail, and technology sectors.

1. Mastering Uncertainty: The Strategic Role of Risk Management 2. Decoding Intelligence: Your Step-by-Step Guide on Artificial Intelligence 3. Machine Learning Foundations: From Theory to Your First Model 4. The Rise of Deep Learning 5. From Generative AI to Context-Aware Intelligence 6. Role of Artificial Intelligence in Risk Management and Vice Versa 7. Managing Emerging Risks Using Python: Your Detailed Guide on How to Enable Ethical AI for Better Data Risk Governance 8. Asking the Right Question: Bridge the Gap Between Risk and Artificial Intelligence 9. Case Study: Your Practical and Stepwise Guide to Build a RAG-Powered AI Assistant 10. Afterword: The Future of Risk Management in the Era of Artificial Intelligence