Trustworthy AI Systems
Engineering Secure, Scalable, and Responsible Intelligence for Real Applications
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Beschreibung
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
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
Autor*in
Vaishnavi Gudur
Themen in »Trustworthy AI Systems«
Trustworthy AI Systems Responsible AI engineering Secure machine learning Ethical AI practices AI compliance frameworks Scalable AI security AI risk management