Responsible AI

CSIRO, Qinghua Lu, Liming Zhu, Jon Whittle, Xiwei Xu

Responsible AI
Format
Paperback
Publisher
Pearson Education (US)
Country
United States
Published
17 January 2024
Pages
320
ISBN
9780138073923

Responsible AI

CSIRO, Qinghua Lu, Liming Zhu, Jon Whittle, 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 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

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