Human-Centered Artificial Intelligence: Research and Applications
Editat de Chang S. Nam, Jae-Yoon Jung, Sangwon Leeen Limba Engleză Paperback – 18 mai 2022
- Presents extensive research on human-centered AI technology
- Provides different methods and techniques used to investigate human-AI interaction
- Discusses open questions and challenges in trust within human-centered AI
- Explores how human-centered AI changes and operates in human-machine interactions
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Specificații
ISBN-13: 9780323856485
ISBN-10: 0323856489
Pagini: 312
Ilustrații: 85 illustrations (60 in full color)
Dimensiuni: 152 x 229 x 22 mm
Greutate: 0.42 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0323856489
Pagini: 312
Ilustrații: 85 illustrations (60 in full color)
Dimensiuni: 152 x 229 x 22 mm
Greutate: 0.42 kg
Editura: ELSEVIER SCIENCE
Public țintă
Graduate students, researchers, academics and professionals in the areas of human factors, robotics, social psychology, neuroscience, computer science, and engineering psychology.Cuprins
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
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