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