AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI provides readers with solutions and a 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 soldiersâ safety in the battlefield, or predicting exports of one country to another) will benefit from the methods presented in this book.
As AI assurance is now a major piece in AI and engineering research, this book will serve as a guide for researchers, scientists and students in their studies and experimentation.
Moreover, as AI is being increasingly discussed and utilized at government and policymaking venues, the assurance of AI systemsâas presented in this bookâis at the nexus of such debates.
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