Overview
AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility. In this timely, practical guide, pioneering AI practitioners bridge these gaps. The authors illuminate issues of AI responsibility across the entire system lifecycle and all system components, offer concrete and actionable guidance for addressing them, and demonstrate these approaches in three detailed case studies. Samples Preview sample pages from Responsible AI: Best Practices for Creating Trustworthy AI Systems > Writing for technologists, decision-makers, students, users, and other stake-holders, the topics cover: Governance mechanisms at industry, organisation, and team levels Development process perspectives, including software engineering best practices for AI System perspectives, including quality attributes, architecture styles, and patterns Techniques for connecting code with data and models, including key tradeoffs Principle-specific techniques for fairness, privacy, and explainability A preview of the future of responsible AI
Full Product Details
Author: CSIRO ,
Qinghua Lu ,
Liming Zhu ,
Jon Whittle
Publisher: Pearson Education (US)
Imprint: Addison Wesley
Dimensions:
Width: 18.90cm
, Height: 1.60cm
, Length: 23.30cm
Weight: 0.570kg
ISBN: 9780138073923
ISBN 10: 0138073929
Pages: 320
Publication Date: 17 January 2024
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Paperback
Publisher's Status: Active
Availability: Available To Order
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Author Information
Dr. Qinghua Lu (Alexandria, Australia) specialises in responsible AI and software engineering for AI-based systems. She leads both Data61's Software Engineering for AI team and CSIRO's Operationalizing Responsible AI Project. Dr. Liming Zhu (Sydney) is a world-leading software architect and software engineering researcher, chairs Australia's blockchain standards committee, and contributes to ISO standards for AI trustworthiness. He leads Data61's Responsible AI initiative and Australia's new National AI Center. With Len Bass and Ingo Weber, Dr. Zhu is a co-author of DevOps: A Software Architect's Perspective. Dr. Jon Whittle (Melbourne) is a world-renowned expert in software engineering and human-computer interaction, with a particular interest in IT for social good, AI research in health sciences, and sustainable development. He leads CSIRO's Data61, Australia's largest digital innovation organisation. Dr. Sherry Xu (Sydney) was recently ranked as the world's fourth most impactful consolidated software engineering researcher. She is the lead author of the first blockchain textbook, Architecture for Blockchain Applications.
