Scaling Responsible AI : From Enthusiasm to Execution

by Noelle Russell

Artificial Intelligence

Book Details

Book Title

Scaling Responsible AI : From Enthusiasm to Execution

Author

Noelle Russell

Publisher

Willy

Publication Date

2025

ISBN

9781394289653

Number of Pages

364

Language

English

Format

PDF

File Size

2.7MB

Subject

Artificial Intelligence

Table of Contents

  • Cover
  • Table of Contents
  • Title Page
  • Introduction
  • What Does This Book Cover?
  • Additional Resources
  • Reflection Questions
  • How to Contact the Publisher or the Author
  • Part I: Day One: The Hype Cycle
  • Chapter 1: LEAD AI: A Framework for Building Responsible AI
  • Chapter 2: The Hype of AI: Capturing the Excitement
  • A Wild Ride: The Initial Excitement of AI
  • Questions Nobody's Asking: What Happens When AI Grows?
  • Looking Cute Today: Benefits That Blind Us
  • Taming the Beast: Partnering with AI Experts
  • Eyes Wide Open: Realistic Expectations
  • Preparing for Tomorrow: Responsible Enthusiasm
  • Takeaways
  • Reflection Questions
  • Chapter 3: Building the AI Sandbox: Safe, Responsible Spaces for Innovation
  • The Basics: What Exactly Is an AI Sandbox?
  • Safe Innovation: Identifying Low-Risk Use Cases
  • Aligning with Values: Ensuring Ethical AI Practices
  • Looking Forward: Scaling Up from Your Sandbox
  • Takeaways
  • Reflection Questions
  • Chapter 4: From Ideation to Action: Setting Up for Successful Business Outcomes
  • Aligning AI with Business Vision and Core Values
  • The Art of Possible: Pushing Boundaries Responsibly
  • Core Value Selection: The Key to Long-Term Success
  • Understanding Organizational Risk
  • Evaluating Risks Systematically
  • Level of Complexity: Avoiding Overcommitment
  • Identifying Minimum Remarkable Products
  • Delighting the User: Ensuring Engagement and Usability
  • Building Inclusive Teams for Better AI Solutions
  • Monitoring and Measuring Systems at Scale for Success and ROI
  • Takeaways
  • Reflection Questions
  • Part II: Day Two: The Road to Reality
  • Chapter 5: From Playground to Production: Embracing the Challenges
  • Bridging the Gap: Transitioning from Proof to Production
  • Infrastructure Matters: Building the Right Foundation
  • Data, Data Everywhere: Managing and Maintaining Quality
  • Tools of the Trade: Picking Your AI Arsenal
  • Metrics that Matter: Measuring Success on “Day Two”
  • Takeaways
  • Reflection Questions
  • Chapter 6: Beyond the Prototype: What Happens After POC?
  • Shifting Mindsets: From Prototype to Production Pilot
  • Ensuring Scalability from the Start: Why It Matters
  • Building a Strong Foundation: Key Technical Considerations
  • Transitioning Smoothly from Pilot to Production
  • Creating a Culture of Continuous Improvement
  • Evaluating Early Successes and Quick Iteration
  • Finding the Balance Between Long-Term Vision and Short-Term Results
  • Preparing for Future Challenges in Scaling AI Solutions
  • Takeaways
  • Reflection Questions
  • Chapter 7: SECURE AI: A Framework for Deploying Responsible AI
  • Understanding the Move: Evaluating AI Initiatives
  • Common Pitfalls: Underestimating Security and Accuracy
  • Scaling Responsibly: Real-Time Performance at Scale
  • Inclusive Testing: The Validation Crucible
  • The Power of Diverse Perspectives: Building for All Users
  • Red Teaming AI: The SECURE AI Framework
  • Blueprint for Success: Avoiding AI Pilot Purgatory
  • Takeaways
  • Reflection Questions
  • Chapter 8: Architecting AI: Designing for Scale and Security
  • Getting Ready to Scale: The Basics of AI Architecture
  • Managing Your AI After Deployment
  • Locking It Down: Building Cybersecurity into Your AI
  • Implementing Best Practices: The Responsible AI Architecture Playbook
  • Looking Forward: Future Trends in Scaling and Securing AI
  • Takeaways
  • Reflection Questions
  • Part III: The AI Journey: Navigating Challenges and Embracing Change
  • Chapter 9: Why Change Is the Only Constant in AI
  • Embracing Uncertainty with Open Arms
  • Identifying Roadblocks Early
  • Turning Challenges into Opportunities
  • Building a Resilient AI Team
  • Adapting Your Strategy on the Fly
  • The Role of Continuous Learning
  • Staying Ahead in a Fast-Paced World
  • Balancing Innovation and Risk
  • Crafting a Forward-Thinking Mindset
  • Takeaways
  • Reflection Questions
  • Chapter 10: Model Evaluation and Selection: Ensuring Accuracy and Performance
  • Chapter 11: Bias and Fairness: Building AI That Serves Everyone
  • Why Bias in AI Is a Big Deal
  • Recognizing Different Types of Bias
  • Tools and Techniques to Detect Bias
  • Strategies for Mitigating Bias
  • Promoting Fairness in Your AI Models
  • Learning from Policy Reviews at All Levels
  • Real-World Examples of Fair AI in Action
  • Looking Ahead: Building Inclusive and Just AI
  • Takeaways
  • Reflection Questions
  • Chapter 12: Responsible AI at Scale: Growth, Governance, and Resilience
  • Why Scaling AI Matters: Beyond the Prototype
  • The Building Blocks of Scalable AI
  • Governance Essentials: Keeping AI Ethical and Compliant
  • Navigating Regulatory Landscapes: What You Must Know
  • Safe and Sound: Creating Robust Governance Frameworks
  • Strengthening the Core: Developing Resilient AI Programs
  • Handling Disruptions Like a Pro
  • Real-World Success Stories: Lessons from the Field
  • Common Pitfalls and How to Avoid Them
  • The Future of Responsible AI at Scale
  • Takeaways
  • Reflection Questions
  • Part IV: The Vision Realized: Leading AI into the Future
  • Chapter 13: Looking Back: Lessons Learned and Insights Gained
  • Gearing Up: Setting the Stage for Future AI Adventures
  • Trailblazers: Stories of AI Innovations Leading the Way
  • AI Communities: Building Bridges and Removing Barriers
  • Human-Centric AI: Ensuring That People Remain at Its Heart
  • Collaborative Ecosystems: Partnerships That Drive Progress
  • Ask the Experts: Wisdom from AI Thought Leaders
  • DIY AI: Empowering Everyone to Be Part of the Journey
  • What's Next: Preparing for the Unpredictable AI Tomorrow
  • Takeaways
  • Reflection Questions
  • Chapter 14: The Future of AI Leadership: Transforming Potential into Power
  • Setting the Stage for Innovation
  • Building a Culture That Thrives on Curiosity
  • Empowering Your AI Teams with Purpose
  • Leading with Clarity Amid Complexity
  • Confidence as a Key to Effective Leadership
  • The Ultimate AI Leadership Checklist
  • Navigating AI's Ethical Landscape
  • Legal Landmines and How to Avoid Them
  • Responsibility and Accountability in AI
  • Charting the Course Ahead: Vision and Values
  • Takeaways
  • Reflection Questions
  • Chapter 15: AI's Impact and Intention: Envisioning a World Transformed
  • The Ripple Effect: AI's Potential for Societal Change
  • AI's Impact on Key Sectors
  • The Journey Ahead
  • AI's Impact on Jobs and the Economy
  • The Promises and Perils of Superintelligence
  • Bridging the Gap: AI in the Fight for Equality
  • What Gives Me Hope
  • The Road Ahead
  • Takeaways
  • Reflection Questions
  • Index
  • Copyright
  • Dedication
  • About the Author
  • Acknowledgments
  • End User License Agreement