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This book explores how trust can be built, maintained, and evaluated in a world increasingly reliant on AI technologies. Designed to be accessible to a broad audience, the book blends theoretical insights with practical approaches, offering readers a comprehensive understanding of the topic.
List of contents
PART I: FOUNDATIONS OF TRUST BUILDING IN THE GENERATIVE ARTIFICIAL INTELLIGENCE ERA 1. Trust Building in the Generative AI - future perspectives and emerging trends 2. Technological and digital challenges for efficient substitution of creative environment in the era of Generative AI 3. Navigating ethical dilemmas: unveiling greenwashing in the AI era 4. Challenges of trust in remote work in the era of Generative AI 5. Generative AI as a driver of trust in innovation 6. Impact of Generative Artificial Intelligence (GAI) on trust and compliance of intelligent automation low-code software PART II: FRAMEWORKS FOR TRUST-BUILDING AND EVALUATION 7. Enhancing cybersecurity: trust dynamics in the age of Generative Artificial Intelligence 8. An overview of tools and methodologies for assessing trust in relation to generative models AI 9. Knowledge assessment in the age of Generative AI 10. Opening the black box: achieving trust through transparency and explainability in Generative AI 11. What will we learn from failures and trust AI applications in organizations? 12. Generative AI in finance - new challenges across trust building needs PART III: CASE STUDIES AND COMPARATIVE ANALYSES 13. Perception of ChatGPT by university students in Poland 14. The potential of using solutions based on Generative Artificial Intelligence in agriculture in European Union countries 15. Trust in Artificial Intelligence - generational differences 16. Trust and integration: AI adoption and socio-technical systems 17. The impact of awareness and risk-benefit perceptions on attitudes towards AI adoption in higher education 18. The limits of intuition in Artificial Intelligence 19. To trust or not to trust: Is Generative Artificial Intelligence taking sides in higher education research? 20. To trust or not to trust: Generative AI-supported academic scientific research publications as a matter of trust and ethics 21. Generative AI use among non-financial companies - trust perspective
About the author
Joanna Paliszkiewicz works as a Full Professor at the Warsaw University of Life Sciences (WULS-SGGW). She is the Director of the Management Institute. She also works for University of Economics Ho Chi Minh City (UEH), Vietnam. She is also an Adjunct Professor at the University of Vaasa in Finland. She obtained academic title "Full Professor" from the International School for Social and Business Studies in Slovenia. She is well recognized in Poland and abroad for her expertise in management issues: knowledge management and trust management. She has published over 220 papers/manuscripts and is the author/cöauthor/editor of 21 books.
Jerzy Göuchowski is a Full Professor at the University of Economics in Katowice. He has served as a Vice¿Rector (2005-2009) and Dean (2009-2019; 2020-now) of the Faculty of Informatics and Communications and he is the Head of the Department of Communication Design and Analysis (since 2017)
Magdalena M¿dra-Sawicka is an Assistant Professor at Warsaw University of Life Sciences (WULS) in the Institute of Economics and Finance. She obtained PhD degree in 2010 and started working at SGGW WULS in 2010 at the Department of Economics and Organization of Enterprises and later in the Department of Finance at the Faculty of Economic Sciences.
Kuanchin Chen is Professor of Computer Information Systems, Director of the Center for Business Analytics, and John W. Snyder Fellow at Western Michigan University. He has more than 25 years of research, teaching, and consulting experience.
