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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
Contents
    Preface.. . . . . . . . . . . . . . . . . xv
     About the Author.. . . . . . . . . . . . . . xix
 Part I Background and Introduction. . . . . . . . . . . . .1
 1 Introduction to Responsible AI. . . . . . . . . 3
     What Is Responsible AI?. . . . . . . . . . . . 4
     What Is AI?. . . . . . . . . . . . . . 6
     Developing AI Responsibly: Who Is Responsible for Putting the
     "Responsible" into AI?.. . . . . . . . . . . . 8
     About This Book.. . . . . . . . . . . . . 9
     How to Read This Book.. . . . . . . . . . . . 11
 2 Operationalizing Responsible AI: A Thought Experiment—Robbie the Robot.. . . . . . . . 13
     A Thought Experiment—Robbie the Robot.. . . . . . . . 13
     Summary. . . . . . . . . . . . . . 22
 Part II Responsible AI Pattern Catalogue. . . . . . . . . . .  23
 3 Overview of the Responsible AI Pattern Catalogue. . . . . 25
     The Key Concepts.. . . . . . . . . . . . . 25
     Why Is Responsible AI Different?. . . . . . . . . . 30
     A Pattern-Oriented Approach for Responsible AI.. . . . . . . 32
 4 Multi-Level Governance Patterns for Responsible AI.. . . . 39
     Industry-Level Governance Patterns. . . . . . . . . 42
     Organization-Level Governance Patterns.. . . . . . . . 56
     Team-Level Governance Patterns.. . . . . . . . . . 72
     Summary. . . . . . . . . . . . . . 85
 5 Process Patterns for Trustworthy Development Processes. . . 87
     Requirements.. . . . . . . . . . . . . 88
     Design. . . . . . . . . . . . . . . 96
     Implementation.. . . . . . . . . . . . . 105
     Testing. . . . . . . . . . . . . . . 110
     Operations. . . . . . . . . . . . . . 114
     Summary. . . . . . . . . . . . . . 120
 6 Product Patterns for Responsible-AI-by-Design.. . . . . 121
     Product Pattern Collection Overview.. . . . . . . . . 122
     Supply Chain Patterns. . . . . . . . . . . . 123
     System Patterns. . . . . . . . . . . . . 134
     Operation Infrastructure Patterns. . . . . . . . . 141
     Summary. . . . . . . . . . . . . . 158
 7 Pattern-Oriented Reference Architecture for Responsible-AI-by-Design. . . . . . . . . 159
     Architectural Principles for Designing AI Systems. . . . . . 160
     Pattern-Oriented Reference Architecture.. . . . . . . . 161
     Summary. . . . . . . . . . . . . . 165
 8 Principle-Specific Techniques for Responsible AI.. . . . . 167
     Fairness.. . . . . . . . . . . . . . 167
     Privacy. . . . . . . . . . . . . . . 172
     Explainability. . . . . . . . . . . . . 178
     Summary. . . . . . . . . . . . . . 182
 Part III Case Studies. . . . . . . . . . . . . . .  183
 9 Risk-Based AI Governance in Telstra. . . . . . . 185
     Policy and Awareness.. . . . . . . . . . . . 186
     Assessing Risk.. . . . . . . . . . . . . 188
     Learnings from Practice. . . . . . . . . . . 192
     Future Work. . . . . . . . . . . . . . 195
 10 Reejig: The World's First Independently Audited Ethical Talent AI.. . . . . . . . . . . 197
     How Is AI Being Used in Talent?.. . . . . . . . . . 198
     What Does Bias in Talent AI Look Like?.. . . . . . . . 200
     Regulating Talent AI Is a Global Issue.. . . . . . . . . 201
     Reejig's Approach to Ethical Talent AI. . . . . . . . . 202
     How Ethical AI Evaluation Is Done: A Case Study in Reejig's World-First Independently Audited Ethical Talent AI. . . . . . . . 204
     Overview.. . . . . . . . . . . . . 204
     Project Overview. . . . . . . . . . . . . 206
     The Ethical AI Framework Used for the Audit.. . . . . . . 207
     The Benefits of Ethical Talent AI.. . . . . . . . . . 210
     Reejig's Outlook on the Future of Ethical Talent AI.. . . . . . 211
 11 Diversity and Inclusion in Artificial Intelligence.. . . . . 213
     Importance of Diversity and Inclusion in AI.. . . . . . . 215
     Definition of Diversity and Inclusion in Artificial Intelligence. . . . 216
     Guidelines for Diversity and Inclusion in Artificial Intelligence. . . . 219
     Conclusion.. . . . . . . . . . . . . . 234
 Part IV Looking to the Future. . . . . . . . . . . . . 237
 12 The Future of Responsible AI.. . . . . . . . . 239
     Regulation. . . . . . . . . . . . . . 241
     Education.. . . . . . . . . . . . . . 242
     Standards.. . . . . . . . . . . . . . 244
     Tools.. . . . . . . . . . . . . . . 245
     Public Awareness.. . . . . . . . . . . . 246
     Final Remarks.. . . . . . . . . . . . . 246
 Part V Appendix. . . . . . . . . . . . . . . . 249
  
 9780138073923, TOC, 11/7/2023

              

