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AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI - Laura Freeman - Bog

Bag om AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI

AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI provides readers with solutions and foundational understanding of the methods that can be applied to test AI systems and provide assurance. Anyone developing software systems with intelligence, building learning algorithms, or deploying AI to a domain-specific problem (such as allocating cyber breaches, analyzing causation at a smart farm, reducing readmissions at a hospital, ensuring soldiers' safety in the battlefield, or predicting exports of one country to another) will benefit from the methods presented in this book. AI assurance is now a major piece in AI and engineering research, and this book serves as a guide to researchers, scientists, and students in their studies and experimentation with AI. Moreover, as AI is being increasingly discussed and utilized at government and policymaking venues, the assurance of AI systems -as presented in this book- is at the nexus of such debates.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9780323919197
  • Indbinding:
  • Paperback
  • Udgivet:
  • 18. oktober 2022
  • 2-3 uger.
  • 16. december 2024
På lager
Forlænget returret til d. 31. januar 2025

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Beskrivelse af AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI

AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI provides readers with solutions and foundational understanding of the methods that can be applied to test AI systems and provide assurance. Anyone developing software systems with intelligence, building learning algorithms, or deploying AI to a domain-specific problem (such as allocating cyber breaches, analyzing causation at a smart farm, reducing readmissions at a hospital, ensuring soldiers' safety in the battlefield, or predicting exports of one country to another) will benefit from the methods presented in this book. AI assurance is now a major piece in AI and engineering research, and this book serves as a guide to researchers, scientists, and students in their studies and experimentation with AI. Moreover, as AI is being increasingly discussed and utilized at government and policymaking venues, the assurance of AI systems -as presented in this book- is at the nexus of such debates.

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