AI Management Framework

In today's rapidly evolving technological landscape, managing artificial intelligence effectively is crucial for both private-sector companies and public-sector organizations. This book provides a robust and ethical framework to guide you through the complexities of AI deployment and management.

This book is your ultimate guide to preparing your organization for AI, developing and operating AI systems, and continuously assessing and improving your AI ecosystem. It introduces a well-tested, practical management system that emphasizes ethical principles and practical solutions.

Designed with practicality in mind, this book offers ready-to-use examples and customizable approaches to fit your organization's unique needs. Whether you are looking to enhance decision-making, improve customer support, or ensure ethical AI practices, this book provides the tools and insights needed to develop, operate, and assess AI systems effectively, regardless of compliance with the ISO AI standard.

What You Will Learn:

• A philosophical framework to ground your AI initiatives.
• Guidance on navigating AI laws and regulations.
• A five-phase AI implementation approach covering preparation, management, development, operation, and assessment.

• Over 31 support tools, including policies, procedures, and ready-made examples of AI plans.
  Who This Book Is for:

  The audience of this book includes CIOs, IT Managers and AI Project Managers, IT development staff, AI and data science professionals, cybersecurity professionals, auditors (IT, Internal, External, etc.), CISOs and corporate security managers, HR managers and staff, compliance and data protection officers, and anyone else interested in using or operating AI systems.

  Unlock the power of AI with a comprehensive management system Prepare, develop, and assess your AI ecosystem Implement a tailored practical AI application

  Autorentext

John Kyriazoglou is currently Editor-in-Chief of "The IIC Internal Controls e-Magazine and represents Western Europe on the Advisory Board of the Institute for Internal Controls. He is also consulting on data privacy and IT security Issues (GDPR, e-Privacy, etc.) to a large number of private and public clients and has published several books on these issues.

John is a business thinker, consultant, and an author. He is a graduate of the University of Toronto, a Certified Internal Controls Auditor (CICA), and a management consultant with more than 40 years of global experience on data management, IT auditing, IT security, IT project management, and data privacy issues. He has written many books (more than 60) on data privacy protection, business management controls, IT, corporate wellness, duty of care, etc.

John has worked in Canada, England, Switzerland, Luxembourg, Greece, Saudi Arabia, and other countries for over 40 years, as a senior IT manager, managing director, IT auditor, and consultant or a variety of clients and projects, in both the private and the public sectors.

Inhalt

Part 1: Foundation.- Chapter 1: AI Management System.- Part 2: AI Ethics Framework.- Chapter 2. The Seven Ancient Greek Wisdom Principles.- Chapter 3: Corporate Philosophy Statements and Policies.- Part 3: AI Regulations and Standards.- Chapter 4: AI Global Standards and Guidelines .- Chapter 5: Major Data Protection Laws and Privacy by Design Framework Principles .- Chapter 6: Digital and Secure AI System Development Guidelines.- Part 4: AI Infrastructure Management.- Chapter 7: Prepare the Organization for AI.- Chapter 8: Establish AI Governance Framework.- Chapter 9: Establish Data Governance Framework.- Chapter 10: Manage IT Governance & Privacy Controls.- Part 5: AI Systems Development and Operations.- Chapter 11: Develop AI Systems.- Chapter 12: Operate AI Systems.- Part 6: AI Infrastructure and Systems Assessment. - Chapter 13: Develop AI Infrastructure and Systems audit process.- Chapter 14: Assess Corporate Governance and HR Management Issues.- Chapter 15: Assess AI Governance and AI Data Management Issues .- Chapter 16: Assess AI Models and AI System Development Issues.- Chapter 17: Assess AI System Operation Issues.- Chapter 18: Assess IT Governance Issues.