Advances in Human-AI Collaboration.

Format:

Book

Author/Creator:

Duffy, Vincent G.

Series:

Advances in Industrial and Systems Engineering Series

Language:

English

Subjects (All):

Artificial intelligence.

Human-computer interaction.

Physical Description:

1 online resource (371 pages)

Edition:

1st ed.

Place of Publication:

Newark : John Wiley & Sons, Incorporated, 2026.

Summary:

Detailed guide on how humans and AI systems work in tandem, focused on the successful deployment and use of applications Advances in Human-AI Collaboration offers a comprehensive exploration of AI technologies and applications in the field of Industrial and Systems Engineering.

Contents:

Cover

Title Page

Copyright

Contents

List of Contributors

Preface

Part I Fundamentals in Human-AI Collaboration

Chapter 1 Human Interaction with Intelligent Automation

1.1 Introduction

1.2 Background

1.2.1 Traditional Automation

1.2.2 Human Interaction with Traditional Automation

1.2.3 Artificial Intelligence

1.2.3.1 Evolution of AI

1.2.3.2 Spectrum of AI

1.3 Human Interaction with Intelligent Automation

1.3.1 AI for Robotic Automation

1.3.2 Augmentation and Adaptation

1.3.3 Levels of AI Assist in Automation

1.3.4 Policy Issues Regarding AI and Automation

1.4 Three Scenarios

1.4.1 Driverless Cars

1.4.2 Management of Autonomous Airplanes

1.4.3 Healthcare Decision Support

1.4.4 Comparison of Scenarios

1.5 Discussion

1.5.1 Continuum of Levels

1.5.2 Transition Management

1.5.3 Human‐Centered Intelligent Automation

1.6 Conclusions

References

Chapter 2 Human-AI Interaction Fundamentals

2.1 Introduction

2.2 Human‐Centered AI

2.2.1 Explainability and Understandability

2.2.2 Equity and Fairness

2.2.3 Human-AI Collaboration

2.2.4 Ethical Considerations

2.3 Interaction Styles

2.3.1 Traditional Interaction Styles in AI

2.3.2 Natural Language Interaction

2.3.3 Gesture‐Based Interaction

2.3.4 Multimodal Interaction Models and Future Trends

2.4 Interaction Contexts

2.4.1 Affective Computing and Interaction with AI

2.4.2 Decision‐Making and Recommender Systems

2.4.3 Generative AI and Large Language Models

2.4.4 Human-Robot Interaction

2.4.5 Application Domains

2.5 HCI Aspects in Human-AI Interaction

2.5.1 Usability and User Experience

2.5.2 Cognitive and Social Factors

2.5.3 Errors and User Trust

2.5.4 Challenges and Limitations

2.6 Summary and Conclusions

References.

Chapter 3 Human-AI Interaction Fundamentals

3.1 Introduction

3.2 Entities Involved in Human-AI Interaction

3.2.1 Humans

3.2.1.1 Demographic and Dispositional Factors

3.2.1.2 Situational and Learned Factors

3.2.2 AI

3.2.3 Environments

3.3 Human-AI Interaction Levels

3.3.1 Coexistence

3.3.2 Cooperation

3.3.3 Collaboration

3.4 Critical Elements of Human-AI Interaction

3.4.1 Trust

3.4.1.1 Trust Spectrum

3.4.1.2 Trust Calibration

3.4.1.3 Trust Measurements

3.4.2 Communication

3.4.3 Privacy and Data Security

3.4.4 Personalization and Adaptability

3.5 Conclusions

Chapter 4 Guidelines for Human-AI Interaction and User Experience

4.1 Introduction

4.2 Social Needs

4.2.1 Laws and Regulations from Selected Regions and Countries

4.2.2 EU AI Act

4.2.3 Chinese Artificial Intelligence Laws

4.2.4 US AI Executive Order 14110

4.2.5 Common Social Needs

4.3 Guidelines to Address Selected Common Social Needs

4.3.1 Ethical Use

4.3.1.1 Social Need Details

4.3.1.2 Guidelines

4.3.2 Product Quality Over Product Lifecycle

4.3.2.1 Social Need Details

4.3.2.2 Guidelines

4.3.3 Human Oversight

4.3.3.1 Social Need Details

4.3.4 Effective, Ethical, Robustness, Accuracy, Safety, and Security

4.3.4.1 Social Need Details

4.3.4.2 Guidelines

4.3.5 Explainability and Trustworthiness

4.3.5.1 Social Need Details

4.3.5.2 Guidelines

4.3.6 Diversity, Fairness, Impartiality, Privacy, Health

4.3.6.1 Social Need Details

4.3.6.2 Guidelines

4.4 Discussion and Future Outlook

4.4.1 Discussion

4.4.2 Outlook

4.4.3 Acknowledgments

4.4.4 Funding

4.4.5 Conflict of Interest

Chapter 5 Human Intelligence vs. Artificial Intelligence

5.1 Characterizing Similarities and Differences Today.

5.1.1 Historical Perspectives of Human Intelligence

5.1.2 Measurement of Human Intelligence

5.1.3 Background on Artificial Intelligence

5.1.4 Similarity and Differences-A Brief Discussion

5.2 Limitations in Human and Artificial Intelligence Today

5.2.1 Perception: Sensory Systems and Sensors

5.2.2 Cognition

5.3 Trustworthiness

Chapter 6 Advances in Human-AI Collaboration

6.1 Introduction

6.1.1 What is an AI Agent?

6.1.1.1 Concept of AI Agent

6.1.1.2 Type of AI Agent

6.1.1.3 Characteristics of AI Agent

6.1.2 Training with AI Support

6.1.2.1 Background

6.1.2.2 Definition of AI Training

6.1.3 Advantages of Training with AI Support

6.1.3.1 Efficiency

6.1.3.2 Personalized

6.1.3.3 Cost Saving

6.1.3.4 Continuous Learning

6.1.4 Challenges and Ethical Considerations in Training with AI Support

6.1.4.1 Transparency and Interpretability

6.1.4.2 Fairness and Bias

6.1.4.3 Other Challenges

6.2 Application of AI in Training

6.2.1 Knowledge Base Construction

6.2.1.1 Concept of Knowledge Base

6.2.1.2 Foundation of Knowledge Base

6.2.2 Training Needs Analysis

6.2.3 Feedback on Training Results

6.2.4 Algorithm Aversion and User Experience

6.3 Case Studies of Training with AI Support

6.3.1 Case Study 1

6.3.2 Case Study 2

6.4 Summary

Acknowledgments

Chapter 7 Human‐AI Teaming

7.1 Theoretical Foundations

7.1.1 Definitions

7.1.2 History and Trends

7.1.3 Theoretical Frameworks for Human-AI Teaming

7.2 Decision‐Making Process in Human-AI Teaming

7.2.1 Division of Labor

7.2.2 Attribution

7.3 Communication in Human-AI Teaming

7.3.1 Factors Influencing Communication in Human-AI Teaming

7.3.2 Benefits and Challenges

7.3.3 Communication Strategies in Human-AI Teaming

7.4 Trust.

7.4.1 Factors Influencing Trust in Human-AI Teaming

7.4.2 The Role of Trust in Human-AI Teaming

7.4.3 Strategies to Enhance Trust in Human-AI Teaming

7.5 Explainability and Explainable AI in Human-AI Teaming

7.5.1 Human-AI Teaming and the Role of Explainability

7.5.2 Challenges and Trends in Explainable AI for Human-AI Teaming

7.6 Ethical and Social Implications

7.6.1 Ethical Dimensions of Human-AI Teaming

7.6.2 Social Implications of Human-AI Teaming

Chapter 8 Human Teaming with Automation and Advanced Agents

8.1 Introduction

8.2 Clarifying Automation and Autonomy

8.3 Teaming Metaphors and Models

8.4 Dynamics of Expertise and Function Allocation

8.5 Challenges in Ascribing Trust Dynamics

8.6 Impacts of Culture and Bias

8.7 Conclusion: Design for Robust and Resilient Human‐Agent Teams

Chapter 9 Integrating Generative Design and Ergonomics: A Data‐Driven Approach with Digital Manikins

9.1 Introduction

9.2 Literature Review

9.2.1 Data‐Driven Generative Design Process

9.2.2 Deep Learning Methods for Cross‐Modal Tasks

9.2.3 Computational Human Factors via Digital Human Modeling

9.3 Methodology

9.3.1 Human‐Centered AI‐Assisted Concept Generation

9.3.2 Concept Evaluation Using Digital Human Modeling

9.3.3 Iterative Concept Refinement and Concept Modification

9.4 Result

9.4.1 Human‐Centered AI‐Assisted Concept Generation

9.4.2 Human‐Centered AI‐Assisted Concept Evaluation

9.5 Discussions

9.6 Conclusions

Part II Application of Human-AI Collaboration

Chapter 10 AI‐Enabled Accessible Travel in Autonomous Vehicles: Promises, Perceptions, and Prototypes

10.1 Introduction

10.2 Travel‐Limiting Disabilities and Challenges with Current Transportation Systems

10.2.1 Travelers with Disabilities.

10.2.2 Aging populations

10.3 Development of Autonomous and Shared Vehicles

10.4 Perceptions of AVs and SAVs

10.4.1 Travelers with Disabilities

10.4.1.1 Mobility Impairments

10.4.1.2 Visual Impairments

10.4.1.3 General (Other Types of Disabilities)

10.4.2 Aging Populations

10.5 Interactions with AVs and SAVs

10.5.1 Travelers with Disabilities

10.5.2 Aging Populations

10.6 Technologies and AI Solutions to Overcome Barriers to Using AVs

10.7 Case Study: The EASI RIDER Innovation

10.8 Future Research and Development Needs

10.9 Conclusion

Chapter 11 Cobot: Collaborative Robots

11.1 The Origins and Development of Collaborative Robots

11.1.1 Overview of Early Industrial Robots

11.1.2 From Industrial Automation to Cobots

11.1.3 The Birth and Evolution of Cobots

11.2 Technical Foundations of Cobots

11.2.1 What Is a Collaborative Robot?

11.2.2 The Role of AI in Cobots

11.2.3 Multimodal Perception Systems

11.2.4 Human-Robot Interaction and Safety Design

11.3 Application Scenarios of Cobots

11.3.1 Cobot Applications in Manufacturing

11.3.2 Cobots in Logistics and Warehousing

11.3.3 Innovative Applications in Healthcare and Service Industries

11.3.4 Cobots in Agriculture and Environmental Management

11.4 The Future of Collaborative Robots

11.4.1 The Integration of Humanoid Robots and Cobots

11.4.2 Ethical, Legal, and Safety Challenges

11.4.3 The Integration of Cobots with Industry 4.0

11.5 Summary

Chapter 12 AI Chat‐Based Customer Services and Systems

12.1 Introduction

12.2 Development of AI Chatbots in Customer Services

12.3 Customer Service Affordances of AI Chatbots

12.4 Factors Affecting Consumer Experience with AI Chatbots

12.4.1 Functional and Utilitarian Features.

12.4.2 Interaction Experience Features.

Notes:

12.4.2 Interaction Experience Features.

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

ISBN:

1-394-26640-5

1-394-26639-1

9781394266395

OCLC:

1579979288