Responsible AI: Best Practices for Creating Trustworthy AI Systems

Responsible AI: Best Practices for Creating Trustworthy AI Systems

by CSIRO, Qinghua Lu, Jon Whittle, Xiwei Xu, Liming Zhu
Released December 2023
Publisher(s): Addison-Wesley Professional
ISBN: 9780138073947

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Book description

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.

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

Table of contents

  1. Cover Page
  2. About This eBook
  3. Halftitle Page
  4. Title Page
  5. Copyright Page
  6. Pearson’s Commitment to Diversity, Equity, and Inclusion
  7. Dedication Page
  8. Contents
  9. Preface
  10. Acknowledgments
  11. About the Authors
  12. Credits
  13. Part I: Background and Introduction
    1. 1. Introduction to Responsible AI
      1. What Is Responsible AI?
      2. What Is AI?
      3. Developing AI Responsibly: Who Is Responsible for Putting the “Responsible” into AI?
      4. About This Book
      5. How to Read This Book
    2. 2. Operationalizing Responsible AI: A Thought Experiment—Robbie the Robot
      1. A Thought Experiment—Robbie the Robot
      2. Summary
  14. Part II: Responsible AI Pattern Catalogue
    1. 3. Overview of the Responsible AI Pattern Catalogue
      1. The Key Concepts
      2. Why Is Responsible AI Different?
      3. A Pattern-Oriented Approach for Responsible AI
    2. 4. Multi-Level Governance Patterns for Responsible AI
      1. Industry-Level Governance Patterns
      2. Organization-Level Governance Patterns
      3. Team-Level Governance Patterns
      4. Summary
    3. 5. Process Patterns for Trustworthy Development Processes
      1. Requirements
      2. Design
      3. Implementation
      4. Testing
      5. Operations
      6. Summary
    4. 6. Product Patterns for Responsible-AI-by-Design
      1. Product Pattern Collection Overview
      2. Supply Chain Patterns
      3. System Patterns
      4. Operation Infrastructure Patterns
      5. Summary
    5. 7. Pattern-Oriented Reference Architecture for Responsible-AI-by-Design
      1. Architectural Principles for Designing AI Systems
      2. Pattern-Oriented Reference Architecture
      3. Summary
    6. 8. Principle-Specific Techniques for Responsible AI
      1. Fairness
      2. Privacy
      3. Explainability
      4. Summary
  15. Part III: Case Studies
    1. 9. Risk-Based AI Governance in Telstra
      1. Policy and Awareness
      2. Assessing Risk
      3. Learnings from Practice
      4. Future Work
    2. 10. Reejig: The World’s First Independently Audited Ethical Talent AI
      1. How Is AI Being Used in Talent?
      2. What Does Bias in Talent AI Look Like?
      3. Regulating Talent AI Is a Global Issue
      4. Reejig’s Approach to Ethical Talent AI
      5. How Ethical AI Evaluation Is Done: A Case Study in Reejig’s World-First Independently Audited Ethical Talent AI
      6. Project Overview
      7. The Ethical AI Framework Used for the Audit
      8. The Benefits of Ethical Talent AI
      9. Reejig’s Outlook on the Future of Ethical Talent AI
    3. 11. Diversity and Inclusion in Artificial Intelligence
      1. Importance of Diversity and Inclusion in AI
      2. Definition of Diversity and Inclusion in Artificial Intelligence
      3. Guidelines for Diversity and Inclusion in Artificial Intelligence
      4. Conclusion
  16. Part IV: Looking to the Future
    1. 12. The Future of Responsible AI
      1. Regulation
      2. Education
      3. Standards
      4. Tools
      5. Public Awareness
      6. Final Remarks
  17. Part V: Appendix
    1. Appendix
      1. Governance Patterns
      2. Process Patterns
      3. Product Patterns
      4. Principle-Specific Techniques
  18. Index

Product information

  • Title: Responsible AI: Best Practices for Creating Trustworthy AI Systems
  • Author(s): CSIRO, Qinghua Lu, Jon Whittle, Xiwei Xu, Liming Zhu
  • Release date: December 2023
  • Publisher(s): Addison-Wesley Professional
  • ISBN: 9780138073947