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Full Description
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.
Contents
Introduction to Trustworthy AI.- Ethical Principles and Global Guidelines.- AI Governance and Risk Management Frameworks.- Security in AI Systems.- Explainable AI: Tools and Techniques.- Robustness and Reliability in Machine Learning.- Bias Detection and Fairness Evaluation.- Responsible Data Engineering.- Trust and Safety in Financial AI Systems.- AI for National Security and Defense.- Autonomous Vehicles and Embedded Systems.- Designing for Human-Centered AI.- Regulatory Compliance and Auditability.- Scaling Trustworthy AI in Startups and Enterprises.- Open Source, Community-Driven Best Practices.- The Future of Trustworthy AI: Trends and Predictions.



