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Evaluating Architectural Safeguards for Uncertain AI Black-Box Components

Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectura...

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Bibliographic Details
Main Author: Scheerer, Max (auth)
Format: Electronic Book Chapter
Language:English
Published: KIT Scientific Publishing 2023
Series:The Karlsruhe Series on Software Design and Quality
Subjects:
Mathematics & science
self-adaptive systems; safeguarding AI; architectural reliability analysis; Software engineering; Selbst-Adaptive Systeme; Absicherung von KI; architekturelle Zuverlässigkeitsanalyse; Softwaretechnik
Online Access:DOAB: download the publication
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Description
Summary:Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectural safeguards for AI components and analyse their effect on the overall system reliability.
Physical Description:1 electronic resource (472 p.)
ISBN:KSP/1000161585
Access:Open Access

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