Scaling Responsible AI : From Enthusiasm to Execution
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
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