Table of Contents
PART I: Explainable AI 1. Are AI models Explainable, Interpretable, and Understandable? 2. Explanation Using Interpretable Models 3. Explanation Using Model-Agnostic Methods 4. Explanation Using Examples 5. Explanation of Ensemble Models 6. Explanation of Deep Learning Models
PART II: User-Centered AI Design and Development Process 7. User-centered explanation interfaces for effective communication between users and AI-based systems 8. Mind perception of human-centered AI: Effects of unfavorable social conditions on user experience of AI 9. Designing user interfaces for AI-based decision support systems
PART III: Applications in Human-AI Interaction 11. Review on recent AI/ML studies about manufacturing systems 12. AI in BCI 13. AI in Human-Robot Interaction 14. AI in Healthcare 15. AI in Decision Making 16. TBD
PART IV: Ethics, Privacy and Policy in Human-AI Interaction 17. Ethics of AI in academic and public discourse 18. Designing explainable artificial intelligence from policy perspectives 19. AI governance 20. TBD