Buch, Englisch, 288 Seiten
Fueling Fast and Effective AI Deployment
Buch, Englisch, 288 Seiten
ISBN: 978-1-394-44558-5
Verlag: John Wiley & Sons Inc
Actionable accountability frameworks for deploying AI at enterprise scale
Accountable AI at Scale: Fueling Fast and Effective AI Deployment delivers practical frameworks for building accountability into AI operations without sacrificing competitive advantage. Written by a former Pentagon Chief AI Officer and the Director of Wharton's Accountable AI Lab, the book reframes accountability not as a constraint on innovation but as the foundation for faster deployment, lower risk, and stronger stakeholder trust across enterprise organizations.
Drawing on hands-on experience driving AI transformation across government and Fortune 500 organizations, the authors reveal what actually works in practice, including failures that have cost companies billions and shaped regulatory policy. The book provides data-driven processes, organizational structures, and cultural norms that operationalize AI accountability, moving leaders beyond aspirational ethics discussions toward measurable, implementable governance systems.
Readers will also find: - Frameworks for balancing AI innovation speed with governance and regulatory compliance across large organizations
- Practical guidance on building organizational structures and cultural norms that address AI risks systematically
- Real-world case studies of AI deployment failures that cost billions and influenced regulatory policy
- Strategies for reframing accountability as a competitive advantage enabling faster, more sustainable AI deployment
- Approaches to operationalizing AI accountability for product managers, engineers, data scientists, and executive leaders
Written for C-suite executives, product managers, engineers, data scientists, and policymakers responsible for AI systems with real consequences, this book provides the operational frameworks needed to deploy AI responsibly at scale while maintaining speed and competitive positioning within evolving regulatory landscapes.
Autoren/Hrsg.
Weitere Infos & Material
Introduction
PART I: THE ESSENTIALS
Chapter 1. AI and Accountability 101
Chapter 2. The Business Case: Accountability Is an Accelerator
Chapter 3. Risk Assessment: Your New Favorite Decision-Making Tool
PART II: THE SIX PILLARS
Chapter 4. Accuracy: Because “Close Enough” Isn’t Always Good Enough
Chapter 5. Fairness: It’s Complicated (But You Still Need to Deal with It)
Chapter 6. Transparency: The Black Box Problem and More
Chapter 7. Misuse: Keeping the Bad Guys Out and the Robots Friendly
Chapter 8. Privacy and Data Protection: Other People’s Data Is Not Your Playground
Chapter 9. Intellectual Property: Who Owns What When Machines Do the Work?
PART III: THE CONSEQUENCES
Chapter 10. Liability: Who Pays When Something Goes Wrong?
Chapter 11. Regulation: The Compliance Environment
Chapter 12. AI’s Societal Impacts: Be Aware of the Big Picture
Chapter 13. Political, Market, Existential, and Environmental Risk: Five Developments to Watch
PART IV: IMPLEMENTATION AND BEYOND
Chapter 14. Know Your Context: What’s Right for You
Chapter 15. Organizational Design: It Takes a Village
Chapter 16. Getting It Done: Tools and Techniques
Conclusion: The Path Forward (Without Destroying Anything)
Appendix: AI Risk Assessment Worksheet
