Responsible AI: Best Practices for Creating Trustworthy AI Systems by Qinghua Lu

Description: Responsible AI by Qinghua Lu, Jon Whittle, Liming Zhu, CSIRO, Xiwei Xu 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 theyre 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 levelsDevelopment process perspectives, including software engineering best practices for AISystem perspectives, including quality attributes, architecture styles, and patternsTechniques for connecting code with data and models, including key tradeoffsPrinciple-specific techniques for fairness, privacy, and explainabilityA preview of the future of responsible AI FORMAT Paperback CONDITION Brand New Author Biography Dr. Qinghua Lu (Alexandria, Australia) specialises in responsible AI and software engineering for AI-based systems. She leads both Data61s Software Engineering for AI team and CSIROs Operationalizing Responsible AI Project. Dr. Liming Zhu (Sydney) is a world-leading software architect and software engineering researcher, chairs Australias blockchain standards committee, and contributes to ISO standards for AI trustworthiness. He leads Data61s Responsible AI initiative and Australias new National AI Center. With Len Bass and Ingo Weber, Dr. Zhu is a co-author of DevOps: A Software Architects 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 CSIROs Data61, Australias largest digital innovation organisation. Dr. Sherry Xu (Sydney) was recently ranked as the worlds fourth most impactful consolidated software engineering researcher. She is the lead author of the first blockchain textbook, Architecture for Blockchain Applications. Table of Contents Part I: Background and Overview 1. What is Responsible AI? 2. Operationalizing Responsible AI Part II: The Process Perspective 3. Governance Perspective and Best Practices 4. Development Process Perspective and Best Practices Part III: The System Perspective 5. From Principles to Quality Attributes 6. Architecture Styles and Design Patterns 7. Beyond Code: Data, Models, Configurations, and Parameters 8. Principle-Specific Techniques Part IV: Case Studies 9. Case Study #1 10. Case Study #2 11. Case Study #3 Part V: Moving into the Future 12. Human and Machines 13. The Future of Responsible AI Details ISBN0138073929 ISBN-10 0138073929 ISBN-13 9780138073923 Format Paperback Imprint Addison Wesley Subtitle Best Practices for Creating Trustworthy AI Systems Place of Publication Boston Country of Publication United States AU Release Date 2024-01-25 NZ Release Date 2024-01-25 Publisher Pearson Education (US) Audience Professional & Vocational UK Release Date 2023-07-07 Year 2024 Author Xiwei Xu Pages 320 Publication Date 2024-01-17 US Release Date 2024-01-17 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:157920926;

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