AI Management System Certification According to the ISO/IEC 42001 Standard: How to Audit, Certify, and Build Responsible AI Systems

Cover
Half Title
Title Page
Copyright Page
Table of Contents
Foreword
Preface
	Generative AI: The Promise, Risks, Challenges, and Opportunities
	Understanding Generative AI
	The Promise and Perils of Generative AI
	Responsible Development and Deployment
	The Generative AI Era
	Conclusion
About the Author and the Contributors
Introduction and Book Organization
Part 1: Artificial Intelligence and Generative AI: Forces behind the Digital Transformation
	Chapter 1: Artificial Intelligence: A Transformational Technology
		Introduction
		Definition of AI
		Different Types of AI
		Artificial Narrow Intelligence (ANI)
		Artificial General Intelligence (AGI)
		Artificial Super Intelligence (ASI)
	Chapter 2: Generative AI: A “Spark from AGI”
		Introduction
		What Is Generative AI
		Generative AI Added Value and Economic Sectors Impacted
		Generative AI Harm, Risk, and Cost
			Emerging (and Unknown) Abilities
			Harmful Content
			Privacy and Data Protection
			Cybersecurity Threat
			Hallucinations
	Chapter 3: Economic Impact of Artificial Intelligence
		Introduction
		Economic Sectors That Will Be Impacted by AI
			The Manufacturing Sector
			The Finance Sector
			The Transportation Industry
			National Security and Law Enforcement Sector
			The Healthcare Sector
			The Cybersecurity Sector
		Strategy Implications: The Current State of AI Adoption
			AI in Automation: RPA
			AI in Prediction: Gaining Cognitive Insight
			AI and Cognitive Engagement: Enhancing Customer Relationship Management
		AI and Robotics
			Industrial Robotics and AI
			Medical Robots
			Military Robots and AI
		Impact of Automation on Society: How Will Society React to AI and Automation?
			Scenario One: Society Will Accept AI
			Scenario Two: Society Will Reject AI
			Scenario Three: Society Will Accept Automation
		The Jobs AI Will Create
			Trainer
			Explainer
			Sustainer
			Countries’ AI National Strategy
	Chapter 4: Digital Transformation: How to Prepare Your Organization for Change
		Introduction
		Digital Transformation Framework
			Leadership Commitment: Building Digital Leadership
			Reskilling and Upskilling
			Teach Critical Thinking Skills
			Teach Innovation
			Build a Customer-Centricity Capability
			Build an Enterprise Agility
			Self-Directed Team to Manage Collaboration
			Agile Process: Review Your Decision-Making Process
Part 2: Artificial Intelligence Management System: How to Put in Place an AI Governance System
	Introduction
	Chapter 5: Clause 4: Context of the Organization
		Introduction: Why Context Analysis Is Crucial to AI Management System?
		What to Include in the Context Analysis
			Competitive Landscape and Stakeholders’ Analysis
			Legal Context Analysis: Laws and Regulations
			The General Data Protection Regulation
			The EU AI Act
				Unacceptable Risk
				High Risk
				Limited Risk
				Low Risk
			The US AI Regulatory Landscape
			The Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence
			Ethical AI: Responsible and Trustworthy AI
			Do No Harm Principle
			The Principle of Fairness and Non-Discrimination
			Human Oversight and Respect of Human Autonomy Principle
			The Principle of Explainability
			The Principle of Robustness
		ISO Certification Process: How to Conduct an Analysis of the Context
			Step 1: Mobilize the Team and Clarify the Mission
			Step 2: Set the Roadmap
			Step 3: Conduct Discovery Sessions
			Step 4: Start with the External Environment
			Step 5: Conduct an Internal Analysis
	Chapter 6: Clause 5: Leadership
		Introduction
			Set the Vision
			Set the Vision, Define the Priorities, and the Strategic Direction
			Lead with Responsible AI Principles (RAI)
			Set the Tone and Use Proactive Communication
		AI Policy: Characteristics and Components
		What Should Be in the AI Policy?
			A Statement on the Scope of the Policy, Its Purpose, and What the Policy Intends to Achieve
			Guidelines on the Use of AI in the Organization
			Show How AI Management System Integrates with Other Management Systems
			Define the Roles and Responsibilities
			Data and Privacy
			AI Compliance
			AI Talent Management
			Monitoring and Improvement
			Review and Alignments
		How Do You Create an AI Policy?
			Form the Team
			Engage with Stakeholders
			Conduct Discovery Sessions and Workshop Meetings with Different Stakeholders
			Review the Laws, Regulations, and Ethical Framework
			AI Strategy
			Step 1: Develop AI Use Case
				Enhancing Customer Satisfaction
				Agile and Data-Driven Decision-Making Process
				Creating Efficiencies
				Improving Productivity
			Step 2: Assess the Competitive Landscape
			Step 3: Reorganize Internally
				Build and Update the Current Technology Infrastructure to Empower the AI Management System
				Design a Data Strategy
				Talent Strategy
			AI Oversight: The Role of Board of Directors
	Chapter 7: Clause 6: Planning
		Introduction
		AI Risk Management, Risk Treatment, and Impact Assessment
			The Concept of Risk
			The Concept of Risk Assessment (Clause 6.1.2)
			The Concept of Risk Treatment (Clause 6.1.3)
			The Concept of Impact Assessment (Clause 6.1.4)
		A Typology of Risks
			Performance Risk
			Security Risk
			Enterprise Risk
			Reputational Risk
			Legal and Regulatory Risk
			AI Scalability Risk
			The Black Box Risk
		AI Risk Management Planning: Principles, Framework, and Process
			AI Risk Framework: A Requirement to Certification
			AI Risk Management Foundations
				AI Risk Should Be Integrated into the Enterprise Risk Management System
				Embrace a Wholistic Perspective
				Customize Your Approach
				Be Inclusive of Your Stakeholders’ View
				Adopt an Agile Mindset
				Spell Out Your Assumptions
				Pay Attention to the Cognitive Bias
				Learn and Improve
		The Planning of Data Management Risk: An Imperative to AI Management System
		ISO Standard Data Quality Requirements
			Data Collection Phase
			Data Preparation Phase
			Problem Framing Phase
		The Planning of Change: AI Management System Change Strategy
			Create a Sense of Urgency
			Build the Guiding Team
			Get the Right Vision
			Communicate for Buy-In
			Empower Teams
			Perseverance
	Chapter 8: Clause 7: Support
		Introduction
		Tangible Resources: The AI Infrastructure
			Computing Performance
			Storage Capacity
			Networking Infrastructure
			Security
		Intangible Resources: AI Competence Model
			What Is a Competence Model?
			AI-Focused Competence Model
				Competence Domain 1: Digital Planning and Design
				Model Competence Domain 2: Data Use and Governance
				Model Competence Domain 3: Digital Management and Execution
				Model Competence’s Attitudes
					Creativity
					Adaptability
					Experimentation
					Curiosity
					Trust
			Awareness (Section 7.3)
			All Employees Need to Be Aware of the AI Policy
				Governance and Leadership
				AI Scope and Objectives
				Use of Responsible AI
				AI Risks
				Data Usage
			How Employees Contribute to a Better Improved AI Management System
				Communication between Different AI Teams
				The Use of Data
				The Need to Reskills and Upskill
			Noncompliance Issues of the AI Management System
		Communication (Clause 7.4)
			Encourage Face-to-Face Communication
			The Medium Is the Message
			Create Policy Champions
		Documented Information
			Documented Information Required: What Needs to Be Documented
	Chapter 9: Clause 8: Operation
		Introduction
		AI Project Life Cycle
			Design Phase: Process Grouping 1
				Identify the Problem
				Select the Idea
				Understand the Context of the Organization
				Conduct a Literature Review
				Frame the Question
			ISO/IEC 42001 Requirements for Process Grouping 1 (Design)
				Responsible AI
				Trustworthy AI
			Design Phase: Process Grouping 2
				Data Collection
				Data Wrangling
			ISO/IEC 42001 Requirements for Process Grouping 2 (Design)
				Data Quality
				Data Resources
			Development Phase: Process Grouping 3
				Build the Model
				Evaluate the Model
			ISO/IEC 42001 Requirements for Process Grouping 3
			Deployment Phase: Process Grouping 4
				Monitor Model Behavior
				Monitor KPIs
			ISO/IEC 42001 Requirements for Process Grouping 4
	Chapter 10: Clause 9: Performance Evaluation
		Introduction
		AI Management System Evaluation and Assessment Requirements
			AI Management System Assessment and Audit
				The Scope of the Performance Evaluation
				Assessment Criteria, Metrics, KPIs
				Large Language Models Audit
			Set Up an Internal Audit Program
			Management Review
	Chapter 11: Clause 10: Improvement
		Introduction
		Corrective Actions and Preventive Actions Framework
		Corrective Actions
		Preventive Actions
		Continual Improvement: The PDCA Approach
		Conclusion
Appendix: 50 Most Important Terms in AI and ISO Standards
Bibliography
Index