Responsible AI: Best Practices for Creating Trustworthy AI Systems

Cover
Half Title
Title Page
Copyright Page
Contents
Preface
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
			Who Should Be Involved in Building Robbie?
			What Are the Responsible AI Principles for Robbie?
			Robbie and Governance Considerations
			Robbie and Process Considerations
			Robbie and Product Considerations
		Summary
Part II: Responsible AI Pattern Catalogue
	3 Overview of the Responsible AI Pattern Catalogue
		The Key Concepts
			The Multifaceted Meanings of Responsible
			Varied Understandings of Operationalization
			The Duality of Trust and Trustworthiness
		Why Is Responsible AI Different?
		A Pattern-Oriented Approach for Responsible AI
	4 Multi-Level Governance Patterns for Responsible AI
		Industry-Level Governance Patterns
			G.1. RAI Law and Regulation
			G.2. RAI Maturity Model
			G.3. RAI Certification
			G.4. Regulatory Sandbox
			G.5. Building Code
			G.6. Independent Oversight
			G.7. Trust Mark
			G.8. RAI Standards
		Organization-Level Governance Patterns
			G.9. Leadership Commitment for RAI
			G.10. RAI Risk Committee
			G.11. Code of RAI
			G.12. RAI Risk Assessment
			G.13. RAI Training
			G.14. Role-Level Accountability Contract
			G.15. RAI Bill of Materials
			G.16. Standardized Reporting
		Team-Level Governance Patterns
			G.17. Customized Agile Process
			G.18. Tight Coupling of AI and Non-AI Development
			G.19. Diverse Team
			G.20. Stakeholder Engagement
			G.21. Continuous Documentation Using Templates
			G.22. Verifiable Claim for AI System Artifacts
			G.23. Failure Mode and Effects Analysis (FMEA)
			G.24. Fault Tree Analysis (FTA)
		Summary
	5 Process Patterns for Trustworthy Development Processes
		Requirements
			P.1. AI Suitability Assessment
			P.2. Verifiable RAI Requirement
			P.3. Lifecycle-Driven Data Requirement
			P.4. RAI User Story
		Design
			P.5. Multi-Level Co-Architecting
			P.6. Envisioning Card
			P.7. RAI Design Modeling
			P.8. System-Level RAI Simulation
			P.9. XAI Interface
		Implementation
			P.10. RAI Governance of APIs
			P.11. RAI Governance via APIs
			P.12. RAI Construction with Reuse
		Testing
			P.13. RAI Acceptance Testing
			P.14. RAI Assessment for Test Cases
		Operations
			P.15. Continuous Deployment for RAI
			P.16. Extensible, Adaptive, and Dynamic RAI Risk Assessment
			P.17. Multi-Level Co-Versioning
		Summary
	6 Product Patterns for Responsible-AI-by-Design
		Product Pattern Collection Overview
		Supply Chain Patterns
			D.1. RAI Bill of Materials Registry
			D.2. Verifiable RAI Credential
			D.3. Co-Versioning Registry
			D.4. Federated Learner
		System Patterns
			D.5. AI Mode Switcher
			D.6. Multi-Model Decision-Maker
			D.7. Homogeneous Redundancy
		Operation Infrastructure Patterns
			D.8. Continuous RAI Validator
			D.9. RAI Sandbox
			D.10. RAI Knowledge Base
			D.11. RAI Digital Twin
			D.12. Incentive Registry
			D.13. RAI Black Box
			D.14. Global-View Auditor
		Summary
	7 Pattern-Oriented Reference Architecture for Responsible-AI-by-Design
		Architectural Principles for Designing AI Systems
		Pattern-Oriented Reference Architecture
		Supply Chain Layer
		System Layer
		Operation Infrastructure Layer
		Summary
	8 Principle-Specific Techniques for Responsible AI
		Fairness
			T.1. Fairness Assessor
			T.2. Discrimination Mitigator
		Privacy
			T.3. Encrypted-Data-Based Trainer
			T.4. Secure Aggregator
			T.5. Random Noise Data Generator
		Explainability
			T.6. Local Explainer
			T.7. Global Explainer
		Summary
Part III: Case Studies
	9 Risk-Based AI Governance in Telstra
		Policy and Awareness
			Telstra’s Definition of AI
			Awareness
		Assessing Risk
			Dimensions of Risk
			Levels of Risk
			Operation of the Risk Council
		Learnings from Practice
			Identifying and Registering Use Cases
			Support from Technology Tools
			Governance over the Whole Lifecycle
			Scaling Up
		Future Work
	10 Reejig: The World’s First Independently Audited Ethical Talent AI
		How Is AI Being Used in Talent?
			Aggregating Siloed Data Across Multiple Sources
			Providing Decision-Making Support at Scale
			Reducing Unconscious Bias
		What Does Bias in Talent AI Look Like?
			Data Bias
			Human Bias
		Regulating Talent AI Is a Global Issue
			US Legislation Being Introduced
			European Legislation Being Introduced
		Reejig’s Approach to Ethical Talent AI
			Debiasing Strategies
		How Ethical AI Evaluation Is Done: A Case Study in Reejig’s World-First Independently Audited Ethical Talent AI
			Overview
			The Independent Audit Approach
			A Summary of the Results
			Recognition and Impact
		Project Overview
			About the Reejig Algorithm
			The Objectives of the Project
			The Approach
		The Ethical AI Framework Used for the Audit
			Ethical Principles
			Ethical Validation
			Functional Validation
		The Benefits of Ethical Talent AI
			Building Stronger and More Diverse Teams by Removing Bias
			Maintaining Privacy and Security
			Demonstrating Leadership Against Competitors
		Reejig’s Outlook on the Future of Ethical Talent AI
			Reejig Has Led the Way in AI Ethics from Day One
			A New Independent Audit of Reejig Is Already Underway
			The Future of Workforce AI Will Unlock Zero Wasted Potential
	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
			Humans
			Data
			Process
			System
			Governance
		Conclusion
			Human
			Data
			Process
			System
			Governance
Part IV: Looking to the Future
	12 The Future of Responsible AI
		Regulation
		Education
		Standards
		Tools
		Public Awareness
		Final Remarks
Part V: Appendix
	Index
		A
		B
		C
		D
		E
		F
		G
		H
		I
		K
		L
		M
		N
		O
		P
		Q
		R
		S
		T
		U
		V
		W
		X
		Y
		Z