This book bridges the gap between leading-edge AI innovation and real deployment, by offering a practical guide to engineering secure, scalable, and responsible AI. The authors describe a unified framework that merges engineering principles with ethical design, cybersecurity, explainability, and policy alignment. Through expert insights, case studies, and technical guidance, the book empowers researchers, developers, and decision-makers to build AI that users can trust.

Provides an interdisciplinary reference on AI security, interpretability, ethics, governance, and reliability
Uniquely combines hands-on engineering strategies with ethical and governance considerations
Enables readers to understand the full lifecycle of trustworthy AI, from model design to post-deployment monitoring