Track Co-Chairs

Yaobin Lu
Professor
luyb@mail.hust.edu.cn
Huazhong University of Science & Technology, China

 

 

 

Ling Zhao
Associate Professor
lingzhao@mail.hust.edu.cn
Huazhong University of Science & Technology, China

 

 

 

Brief Introduction

This track addresses emerging IS research issues driven by artificial intelligence. The typical applications of AI include Intelligent Personal Assistant (IPA), autonomous vehicles, facial recognition, and natural language processing etc. As a transformational technology, AI is now exerting deep impacts on different levels, including individuals, organizations, and society. For individual consumers, it becomes quite common to access AI-driven products or services in their daily life, e.g., Intelligent Personal Assistant (IPA), Intelligent Customer Service. Consumers have to interact with AI robots rather than human service personnel. Thus, it raises new research questions related to changing consumer behavior under AI context, e.g, how consumer interact with AI, how consumer make decisions assisted by AI, and how AI persuade consumers, and so on. For companies who embrace AI for business innovation, are facing challenges that how to utilize and mange AI in the organizations. For instance, service innovation enables by AI implies the way how services designed, delivered and evaluated would be quite different with traditional services. Though AI implies more personalized recommendation and less human cost based on sophisticated algorithms from one side, increasing algorithm training cost and changing consumers’ behavior are still challenges from the other side. Moreover, organizations that adopt AI technologies also have to deal with issues related to allocation of AI and human resources, managerial challenges caused by synergy and dissynergy between AI and human employees. From the society level, AI is continually changing our social structure, laws, and culture. The application of AI increases concerns about rights of robot, privacy, discrimination caused by algorithm bias.

Thus, this track focuses on new IS research questions emerging from different levels with the applications of AI. We welcome research from any empirical and theoretical standpoint. We welcome research that uses a wide variety of methods, including qualitative methods, large-scale data analysis, surveys, digital field experiments, simulations and multi-methods. We are particularly interested in papers that raise interesting questions and challenge current IS related conceptualizations which might not be applicable in the AI context.

Topics

1. Psychological, social and cultural aspects of human-machine interactions
2. Challenges of consumer decision making assisted by AI
3. The changing of consumer behavior in AI context
4. Theories of AI-fostered service innovations, including smart product development and software development
5. Paradoxical effects of AI technologies on organizational activity
6. Emergence and evolution of platforms, ecosystems, and markets shaped by AI technologies
7. The competition and collaboration between firms in the AI-driven ecosystems
8. Emergence of collaboration between human service staff and AI and their impact on working and organizing
9. Privacy and information security in the context of AI

10. Ethical, moral, and societal implications of AI

11. Data analysis methods and algorithms in the AI context