Description
AI, Responsibility, and Human Judgment
Why Answerability Matters When Intelligence Systems Work Too Well
Stammberger, Iris
ISBN 978-3-032-38487-4 · Springer · XXV, 193 p. 3 illus. ·
Description / Beschreibung
In today's complex institutions, responsibility can become vague even when professionals do everything "right." This book explains why many failures are not caused by bad actors or poor skills, but rather by decision systems that function smoothly while leaving no one clearly accountable for their outcomes. As algorithms, dashboards, and standardized workflows influence more of our decisions, traditional notions of professional responsibility no longer align with the scale and speed of modern practices.
By introducing the concept of answerability as a central professional capacity, the book demonstrates how good decisions depend on staying responsive to the real human and material consequences of actions, especially when rules and roles offer no guidance. Through real-life examples, the book reveals how seemingly successful outcomes can be problematic, how apparently compliant decisions can undermine care, and how high-performing systems can quietly erode accountability.
Designed for professionals and policymakers, the book offers practical tools to strengthen judgment, attention, and modern wisdom in an age of AI-driven governance.
Contents / Inhaltsverzeichnis
Chapter 1. Introduction.- Part I: Orientation and Human Judgment.- Chapter 2. Orientation, Expertise, and Human Judgment.- Chapter 3. The Frames That Define Responsibility.- Chapter 4. When Optimization Narrows the World.- Part II: When Responsibility Is Not Enough.- Chapter 5. When Responsibility Is Not Enough.- Chapter 6. When Responsibility and Answerability Diverge.- Part III: AI and the Acceleration of Frame Drift.- Chapter 7. AI as Frame Drift Amplifier.- Chapter 8. The Loss of Reflective Slack.- Part IV: Cultivating Professional Answerability.- Chapter 9. Professional Orientation as Competence.- Chapter 10. Designing for Answerability.- Part V: Conclusion.- Chapter 11. Remaining Answerable.
Contributors / Mitwirkende
Iris Stammberger is an organizational consultant, cognitive scientist, and educator whose work sits at the crossroads of human intelligence, technology, and decision-making. She studies how tools, institutions, and sociotechnical systems shape perception, judgment, and moral responsibility—especially as AI becomes embedded in everyday practice. Stammberger has worked internationally across higher education, international development, engineering, and biotechnology, advising both private and public organizations. She also leads professional development programs and organizational change workshops that help practitioners navigate complex decision environments.
Features / Besonderheiten
Illustrates how modern decision systems quietly erode accountability, even when professionals act correctly
Equips readers with practical tools to recognize and counter the loss of responsibility in complex institutions Shows why cultivating answerability is essential for sound judgment and governance in the age of AI
