Responsible AI: Best Practices for Creating Trustworthy AI Systems (Early Release) 9780138073947, 9780138073923, 0138073929

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

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