Full Description
In an age in which AI systems increasingly shape our everyday lives, our educational environments, and our workplaces, one question becomes central: How do we build trust in them?
An enhanced translation of the 2024 German edition published by Springer Vieweg Wiesbaden, this groundbreaking book offers a comprehensive exploration of trust in artificial intelligence from organizational, educational, technical, and societal perspectives, with a particular focus on the transformative role of AI in higher education.
As systems like ChatGPT and Claude raise fundamental questions about the evolving relationship between humans and machines, this book provides essential guidance for leaders, educators, developers, and policymakers in both German- and English-speaking contexts. Renowned experts contribute interdisciplinary insights that blend theory with practical case studies, ranging from AI-supported decision-making in organizations to trustworthy AI applications in universities, student support systems, and teaching-learning processes.
Of particular value are the concrete frameworks for human-centered AI design, in-depth analyses of fairness and transparency criteria, and cultural studies perspectives that illuminate the paradoxes of trusting technological systems. Readers will gain not only a deeper understanding of the psychological and ethical dimensions of AI trust, but also actionable strategies for designing and implementing trustworthy AI in their own fields - including practical approaches for higher-education institutions navigating the AI transformation.
While a certain familiarity with basic AI concepts would ease the reading experience, the book also provides accessible entry points for newcomers interested in understanding how trust can be built in the technologies that increasingly shape our future.
Contents
"Foreword to the German Edition".- "Preface.- List of Contributors".- "1.Introduction".- "Part I. Organizational Perspectives".- "2. Artificial Intelligence - Our Best Friend? - How People React to AI Decision Recommendations".- "3. Trust, Humans, Machines - On Institutional Trust and Confidence Building Measures".- "4.Trust as an Enabler of the AI Value Creation Cycle - Design Implications from a Systems Theory Perspective".- "5. The Psychology of Organizational Trust in AI.- Part II. Educational Perspectives".- "6. My Colleague, AI - How Artificial Intelligence Is Transforming Teaching and Learning in Schools".- "7. Trustworthy AI - A Discussion from a Psychological and Educational Perspective".- "8. The Ethics of AI in Universities: Navigating Quality, Identity and Privacy".- "9. Can ChatGPT Be Trusted in Physics Research and Teaching?".- "10. Trust-Building Measures Using the Example of AI Applications in Higher Education".- "11. Developing RAG-Based Chatbots: A Framework for Applications in Higher Education.- Part III. Technical Perspectives".- "12. Bayesian Networks for Implementing Transparent, Explainable, and Trustworthy AI".- "13. Fairness in AI Systems".- "14. The Human at the Center: Insights into Designing Human-Centered Artificial Intelligence".- "15. Artificial Intelligence as a Trustworthy Mentoring System in Adult Education.- Part IV. Societal Perspectives".- "16. Trustworthy AI - A Paradoxical Matter".- "17. Trust in AI - Cultural Studies and Media Perspectives".- "18. Gamechanger AI in Sport and Training Science - Can We Trust the Technology Yet?".
