Advances in Human-AI Collaboration

VINCENT G. DUFFY is a Professor of Industrial Engineering and Agricultural & Biological Engineering at Purdue University. WALDEMAR KARWOWSKI is a Pegasus Professor and Chairman in the Department of Industrial Engineering and Management Systems at the University of Central Florida. GAVRIEL SALVENDY is a University Distinguished Professor at the University of Central Florida.

• List of Contributors xviiPreface xxiSection I Fundamentals in Human–AI Collaboration 11 Human Interaction with Intelligent Automation: A Continuum of AI Levels from Which Designers and Users Can Choose 3Thomas B. Sheridan and William B. Rouse1.1 Introduction 31.2 Background 31.3 Human Interaction with Intelligent Automation 71.4 Three Scenarios 101.5 Discussion 131.6 Conclusions 152 Human–AI Interaction Fundamentals 17George Margetis, Stavroula Ntoa, Asterios Leonidis, and Constantine Stephanidis2.1 Introduction 172.2 Human-Centered AI 182.3 Interaction Styles 222.4 Interaction Contexts 252.5 HCI Aspects in Human–AI Interaction 282.6 Summary and Conclusions 313 Human–AI Interaction Fundamentals 41Woei-Chyi Chang, Sogand Hasanzadeh, and Vincent G. Duffy3.1 Introduction 413.2 Entities Involved in Human–AI Interaction 413.3 Human–AI Interaction Levels 443.4 Critical Elements of Human–AI Interaction 453.5 Conclusions 514 Guidelines for Human–AI Interaction and User Experience 57Helmut Degen4.1 Introduction 574.2 Social Needs 594.3 Guidelines to Address Selected Common Social Needs 654.4 Discussion and Future Outlook 815 Human Intelligence vs. Artificial Intelligence 91Peiran Liu and Denny Yu5.1 Characterizing Similarities and Differences Today 915.2 Limitations in Human and Artificial Intelligence Today 965.3 Trustworthiness 1006 Advances in Human–AI Collaboration: Training with AI Support 107Yubin Xie, Siu Shing Man, Ronggang Zhou, and Alan Hoi Shou Chan6.1 Introduction 1076.2 Application of AI in Training 1136.3 Case Studies of Training with AI Support 1176.4 Summary 1187 Human-AI Teaming 123Tianyi Yuan, Minqian Yang, Dian Yu, and Pei-Luen Patrick Rau7.1 Theoretical Foundations 1237.2 Decision-Making Process in Human–AI Teaming 1267.3 Communication in Human–AI Teaming 1287.4 Trust 1307.5 Explainability and Explainable AI in Human–AI Teaming 1327.6 Ethical and Social Implications 1338 Human Teaming with Automation and Advanced Agents 143Barrett S. Caldwell, Rua M. Williams, and C. Nuela Enebechi8.1 Introduction 1438.2 Clarifying Automation and Autonomy 1448.3 Teaming Metaphors and Models 1468.4 Dynamics of Expertise and Function Allocation 1488.5 Challenges in Ascribing Trust Dynamics 1518.6 Impacts of Culture and Bias 1528.7 Conclusion: Design for Robust and Resilient Human-Agent Teams 1549 Integrating Generative Design and Ergonomics: A Data-Driven Approach with Digital Manikins 159H. Onan Demirel, Xingang Li, and Zhenghui Sha9.1 Introduction 1599.2 Literature Review 1619.3 Methodology 1639.4 Result 1659.5 Discussions 1679.6 Conclusions 169Section II Application of Human–AI Collaboration 17310 AI-Enabled Accessible Travel in Autonomous Vehicles: Promises, Perceptions, and Prototypes 175Brandon J. Pitts, Qiyue Wang, and Bradley S. Duerstock10.1 Introduction 17510.2 Travel-Limiting Disabilities and Challenges with Current Transportation Systems 17610.3 Development of Autonomous and Shared Vehicles 17710.4 Perceptions of AVs and SAVs 17910.5 Interactions with AVs and SAVs 18210.6 Technologies and AI Solutions to Overcome Barriers to Using AVs 18510.7 Case Study: The EASI RIDER Innovation 18810.8 Future Research and Development Needs 19310.9 Conclusion 19311 Cobot: Collaborative Robots 201Li Liu11.1 The Origins and Development of Collaborative Robots 20111.2 Technical Foundations of Cobots 20411.3 Application Scenarios of Cobots 20711.4 The Future of Collaborative Robots 21111.5 Summary 21412 AI Chat-Based Customer Services and Systems 217Qin Gao and Jinhan Zhang12.1 Introduction 21712.2 Development of AI Chatbots in Customer Services 21812.3 Customer Service Affordances of AI Chatbots 21912.4 Factors Affecting Consumer Experience with AI Chatbots 22512.5 Impacts of AI Chatbots on Customer Service Experience 22912.6 AI Chatbot in Public Services 23012.7 Challenges of Using AI Chatbot 23212.8 Conclusions 23313 AI in Healthcare and Medicine 239Tianrong Chen, Zhenzhen Xie, and Calvin Or13.1 Introduction 23913.2 What Is AI? 24013.3 AI in Healthcare 24113.4 AI in Medicine 24513.5 Considerations and Challenges 24913.6 Future Trends and Opportunities 25213.7 Conclusions 25214 AI in Human Resource Management 263Xinyu Fu, Fiona Fui-Hoon Nah, Songbo Liu, Kairui Zhang, Zixin Huang, Ruilin Zheng, and Weiqi Xie14.1 AI-Driven Human Resource Processes 26414.2 How AI Reshapes Team Dynamics 27214.3 Ethical Considerations and Challenges 27415 Kansei Engineering: Current Challenges and Future Trends with Advances in Artificial Intelligence 287Qing-Xing Qu, Fu Guo, and Vincent G. Duffy15.1 Introduction 28715.2 Advances in Intelligence Product Development 28915.3 Kansei Design in Different Interaction Modalities 29215.4 Challenges Encountered and Opportunities for Future Research 29515.5 Conclusions 29616 AI in Collaborative Writing 303Nina Jiang and Vincent G. Duffy16.1 Introduction 30316.2 Literature Review 30416.3 Fundamentals in Machine Learning and Text Generation 30916.4 User Perception of the Machine Role 31116.5 Strategies for Moving Beyond Passive Writing Assistance 31316.6 Collaborative Writing Best Practice Examples 31416.7 Discussion 31516.8 Conclusion 31817 Addressing AI Vulnerabilities Through Human-Centered Approaches and Risk Frameworks 325Sarvesh Sawant, Aasish Bhanu, Beau G. Schelble, and Kapil Chalil Madathil17.1 Introduction 32517.2 Types of AI Vulnerabilities 32817.3 Mitigating AI Vulnerabilities Through Human-Centered Design 33117.4 Summary 335References 335Index 341