Causal Artificial Intelligence

Table of Contents

1. Cover
2. Table of Contents
3. Title Page
4. Foreword
5. Preface
6. Introduction
7. CHAPTER 1: Setting the Stage for Causal AI
   1. Why Causality Is a Game Changer
   2. Causal AI in Perspective with Analytics
   3. Analytical Sophistication Model
   4. Scope of Services to Support Causal AI
   5. The Value of the Hybrid Team
   6. The Promise of AI
   7. Understanding the Core Concepts of Causal AI
   8. Summary
   9. Note
8. CHAPTER 2: Understanding the Valueof Causal AI
   1. Defining Causal AI
   2. The Origins of Causal AI
   3. Why Causal AI Is the Next Generation of AI
   4. The Business Imperative of a Causal Model
   5. The Importance of Augmented Intelligence
   6. The Importance of Data, Visualization, and Frameworks
   7. Getting Started with Causal AI
   8. Summary
   9. Notes
9. CHAPTER 3: Elements of Causal AI
   1. Conceptual Models
   2. Process Models
   3. Collaboration Between Business and Analytics Professionals
   4. The Fundamental Building Blocks of Causal AI Models
   5. The Elements of Visual Modeling
   6. Summary
   7. Notes
10. CHAPTER 4: Creating Practical Causal AI Models and Systems
    1. Understanding Complex Models
    2. Causal Modeling Process: Part 1
    3. Causal-Based Approach: Part 2
    4. Summary
    5. Notes
11. CHAPTER 5: Creating a Model with a Hybrid Team
    1. The Hybrid Team
    2. Defining Roles
    3. The Basics Steps for a Hybrid Team Project
    4. An Overview of Model Creation
    5. Summary
12. CHAPTER 6: Explainability, Bias Detection, and AI Responsibility in Causal AI
    1. Explainability
    2. Detecting Bias and Ensuring Responsible AI
    3. Summary
    4. Note
13. CHAPTER 7: Tools, Practices, and Techniques to Enable Causal AI
    1. The Causal AI Pipeline
    2. The Importance ...