Responsible Artificial Intelligence for Critical Engineering Infrastructure
Theory, Methods, and Applications
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Beschreibung
This edited volume provides a comprehensive and multidisciplinary exploration of responsible artificial intelligence (AI) as it is applied to critical infrastructure systems. These include high-risk domains such as chemical plants, nuclear facilities, and energy generation systems, where the safe and ethical use of AI is not optional but essential.
The book brings together perspectives from multiple branches of engineering, including computer, mechanical, chemical, nuclear, and systems engineering, to illustrate how responsible AI can be embedded in complex, interconnected industrial environments. It addresses core topics such as algorithmic fairness, explainability, AI safety, risk assessment, and ethical governance, all framed within practical, real-world applications.
Bridging the gap between theoretical frameworks and real-world implementation, the book offers theoretical foundations, advanced algorithms, and applied case studies to support the development of AI systems that are transparent, accountable, and trustworthy. Moreover, by connecting technical innovation in AI with domain-specific challenges across engineering disciplines, this volume addresses a critical and timely need for guidance on how to responsibly design and deploy AI systems in infrastructures where failure is not an option.
In addition, this book:
- Addresses a critical and timely need for guidance on how to design and deploy AI systems in infrastructures responsibly
- Covers critical high-risk systems including chemical plants, nuclear facilities, and energy generation systems
- Written by a diverse and interdisciplinary authorship from academia and industry in various countries
This edited volume provides a comprehensive and multidisciplinary exploration of responsible artificial intelligence (AI) as it is applied to critical infrastructure systems. These include high-risk domains such as chemical plants, nuclear facilities, and energy generation systems, where the safe and ethical use of AI is not optional but essential.
The book brings together perspectives from multiple branches of engineering, including computer, mechanical, chemical, nuclear, and systems engineering, to illustrate how responsible AI can be embedded in complex, interconnected industrial environments. It addresses core topics such as algorithmic fairness, explainability, AI safety, risk assessment, and ethical governance, all framed within practical, real-world applications.
Bridging the gap between theoretical frameworks and real-world implementation, the book offers theoretical foundations, advanced algorithms, and applied case studies to support the development of AI systems that are transparent, accountable, and trustworthy. Moreover, by connecting technical innovation in AI with domain-specific challenges across engineering disciplines, this volume addresses a critical and timely need for guidance on how to responsibly design and deploy AI systems in infrastructures where failure is not an option.
Addresses a critical and timely need for guidance on how to design and deploy AI systems in infrastructures responsibly Covers critical high-risk systems including chemical plants, nuclear facilities, and energy generation systems Written by a diverse and interdisciplinary authorship from academia and industry in various countries
Autor*in
Rajeevan Arunthavanathan
Themen in »Responsible Artificial Intelligence for Critical Engineering Infrastructure«
responsible artificial intelligence critical infrastructure responsible AI in engineering algorithmic fairness explainability AI safety risk assessment ethical governance