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Innovations in Artificial Intelligence and Human-Computer Interaction in the Digital Era

1st Edition - July 22, 2023

Editors: Surbhi Bhatia Khan, Suyel Namasudra, Swati Chandna, Arwa Mashat

Paperback ISBN:

9 7 8 - 0 - 3 2 3 - 9 9 8 9 1 - 8

eBook ISBN:

9 7 8 - 0 - 3 2 3 - 9 9 9 4 9 - 6

Innovations in Artificial Intelligence and Human Computer Interaction in the Digital Era investigates the interaction and growing interdependency of the HCI and AI fields, which… Read more

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Innovations in Artificial Intelligence and Human Computer Interaction in the Digital Era investigates the interaction and growing interdependency of the HCI and AI fields, which are not usually addressed in traditional approaches. Chapters explore how well AI can interact with users based on linguistics and user-centered design processes, especially with the advances of AI and the hype around many applications. Other sections investigate how HCI and AI can mutually benefit from a closer association and the how the AI community can improve their usage of HCI methods like “Wizard of Oz” prototyping and “Thinking aloud” protocols.

Moreover, HCI can further augment human capabilities using new technologies. This book demonstrates how an interdisciplinary team of HCI and AI researchers can develop extraordinary applications, such as improved education systems, smart homes, smart healthcare and map Human Computer Interaction (HCI) for a multidisciplinary field that focuses on the design of computer technology and the interaction between users and computers in different domains.

Cover image
Title page
Table of Contents
Copyright
List of contributors
Biographies
Preface
Chapter 1. Introduction to human-computer interaction using artificial intelligence
1.1. Introduction
1.2. Human-Computer interaction and its importance
Chapter 2. Augmented and immersive virtual reality to train spatial skills in STEAM university students
2.1. Introduction
2.2. Employing virtual and augmented reality
2.3. Motivation and contribution
2.4. Methodology
2.5. Results
2.6. Discussion
2.7. Conclusions and future works
Chapter 3. Introduction to artificial intelligence and current trends
3.1. Introduction
3.2. History of AI
3.3. Industry 4.0 and AI revolution
3.4. Explainable AI
3.5. Applicability of AI in recommendation systems
3.6. Advantages and disadvantages of AI
3.7. Symbolic AI and computational AI
3.8. Evolutionary computing
3.9. Logic-based reasoning
3.10. Models of knowledge representation based on structural analysis
3.11. Rule-binding systems
3.12. Pattern recognition and cluster analysis
3.13. Neural networks
3.14. AI applications
3.15. Intelligent robots
3.16. AI research prospects and future directions
3.17. Conclusions
Chapter 4. Computational intelligence in human-computer interaction–Case study on employability in higher education
4.1. Introduction
4.2. Case study in higher education system
4.3. Background
4.4. Proposed framework: solution with artificial intelligence and human-computer interaction
4.5. Results and conclusion
Chapter 5. Human-centered artificial intelligence
5.1. Introduction to human-centered AI
5.2. Human-in-the-loop machine learning, reasoning, and planning
5.3. Data analysis
5.4. Designing and prototyping
5.5. Evaluation and strategies
5.6. Case studies
5.7. Limitations of HAI
5.8. Conclusion
Chapter 6. Strategies for efficient and intelligent user interfaces
6.1. Introduction
6.2. Strategies required for efficient intelligent user interfaces
6.3. Recent innovations in intelligent user interfaces
6.4. Conclusions and future work
Chapter 7. Uses of artificial intelligence with human-computer interaction in psychology
7.1. Introduction
7.2. Preliminaries
7.3. Role of HCI and AI in psychology
7.4. User-centered system development
7.5. Usability engineering and verification
7.6. Democratization of information technology
7.7. Challenges
7.8. Conclusion and future scope
7.9. Discussion
Chapter 8. Managing postpandemic effects using artificial intelligence with human-computer interaction
8.1. Introduction
8.2. Background studies
8.3. Managing effects of work from home
8.4. Managing effects of blended learning
8.5. Managing effects of eLearning
8.6. Discussion
8.7. Conclusions and future works
Chapter 9. Practical case studies on human-computer interaction
9.1. Introduction
9.2. Healthcare systems
9.3. Digital hearing
9.4. Digital humanities
9.5. Business intelligence
9.6. Case studies
9.7. Conclusion
Chapter 10. Design and development of applications using human-computer interaction
10.1. HCI design principles
10.2. Designing VR applications
10.3. Designing automotive applications
10.4. Designing healthcare applications
10.5. Designing airline applications
10.6. HCI for emergencies
10.7. Conclusion
Chapter 11. Challenges and future work directions in artificial intelligence with human-computer interaction
11.1. Introduction
11.2. Research challenges in AI with HCI
11.3. HCI for speech-impaired people: a case study
11.4. Beyond HCI
11.5. Future work directions in AI with HCI
11.6. Conclusions
Index

Surbhi Bhatia Khan

Surbhi Bhatia Khan is Doctorate in Computer Science and Engineering in the area of Machine Learning and Social Media Analytics. She earned Project Management Professional Certification from reputed Project Management Institute, USA. She is currently working in the Department of Data Science, School of Science, Engineering and Environment, University of Salford, Manchester, United Kingdom. She has more than 11 years of academic and teaching experience in different universities. She is the awardee of the Research Excellence award given by King Faisal University, Saudi Arabia, in 2021. She has published 100þ papers in many reputed journals in high indexed outlets. She has around 12 international patents from India, Australia, and the United States. She has successfully authored 3 books and has also edited 12 books. She has completed many projects approved from Ministry of Education, Saudi Arabia, and Deanship of Scientific Research in different universities in Saudi Arabia and from India. Her area of interest is Knowledge Management, Information Systems, Machine Learning, and Data Science.

Affiliations and expertise

Assistant Professor, Department of Data Science, School of Science, Engineering and Environment, University of Salford, Manchester, United Kingdom

Suyel Namasudra

Suyel Namasudra has received PhD from the National Institute of Technology Silchar, Assam, India. He was a Postdoctorate Fellow at the International University of La Rioja (UNIR), Spain. Currently, Dr. Namasudra is working as an Assistant Professor in the Department of Computer Science and Engineering at the National Institute of Technology Agartala, Tripura, India. Before joining the National Institute of Technology Agartala, Dr. Namasudra was an Assistant Professor in the Department of Computer Science and Engineering at the National Institute of Technology Patna, Bihar, India. His research interests include blockchain technology, cloud computing, IoT, AI, and DNA computing. Dr. Namasudra has edited 4 books, 5 patents, and 75 publications in conference proceedings, book chapters, and refereed journals like IEEE TII, IEEE T-ITS, IEEE TSC, IEEE TCSS, IEEE TCBB, ACM TOMM, ACM TOSN, ACM TALLIP, FGCS, CAEE, and many more. He has served as a Lead Guest Editor/Guest Editor in many reputed journals like ACM TOMM (ACM, IF: 3.144), MONE (Springer, IF: 3.426), CAEE (Elsevier, IF: 3.818), CAIS (Springer, IF: 4.927), CMC (Tech Science Press, IF: 3.772), Sensors (MDPI, IF: 3.576), and many more. Dr. Namasudra is the Editor-in-Chief of the Cloud Computing and Data Science (ISSN: 2737-4092 (online)) journal, and he has participated in many international conferences as an organizer and session Chair. He is a member of IEEE, ACM, and IEI. Dr. Namasudra has been featured in the list of the top 2% scientists in the world in 2021 and 2022, and his h-index is 29.

Affiliations and expertise

Assistant Professor, Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India

Swati Chandna

Swati Chandna is working as a full-time Professor for Data Science at SRH University Heidelberg, Germany. Additionally, she is the Program Director of the master’s in applied data science and analytics program. Earlier from January 2018 till March 2020 she was working as a guest professor at SRH University Heidelberg. In parallel, she was also working as a full-time senior data scientist and has worked for various renowned customers in automobile, heat, and airline industry. From 2013 until 2018, she has worked as a computer scientist at Karlsruhe Institute of Technology, Karlsruhe, Germany, in the area of digital humanities. Her scientific profile includes artificial intelligence, big data analytics, data visualization, natural language processing, machine learning, and data storytelling. She has authored and co-authored many research papers published in various national and international journals and conferences.

Affiliations and expertise

Professor of Information, Media and Design, SRH University Heidelberg, Heidelberg, Germany

Arwa Mashat

Arwa Mashat is an Assistant Professor in the Information System department in the Faculty of Computing and Information Technology, King Abdulaziz University, Rabigh, Saudi Arabia. She received her Bachelor degree in Computer Science from King Abdulaziz University, Jeddah, her Master’s degree in Educational Technology from Youngstown State University, Ohio, USA, and her PhD in Instructional Design and Technology from Old Dominion University in USA. Currently, she is the Vice Dean for the Applied College and the Vice Dean for the Faculty of Computing and Information Technology in King Abdulaziz University, Rabigh, Saudi Arabia. Her research interests include eye tracking, education technology, online learning, artificial intelligence, and Internet of Things.

Affiliations and expertise

Assistant Professor, Faculty of Computing and Information Technology, King Abdulaziz University, Rabigh, Saudi Arabia