Track Co-Chairs

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

 

 

 

 

 

Zilong Liu
Professor
Zilonglord@126.com
Dongbei University of Finance & Economics

 

 

 

 

Aihui Chen
Associate Professor
aihui@tju.edu.cn
Tianjin University

 

 

 

 

 

Brief Introduction

As the goal pursued in the evolution of human-AI collaboration, Human-AI integration is conducive to the healthy and long-term development of AI-powered traditional or new form of organizations. However, this process requires human employees and AI to progress and evolve together and there are two-fold challenges that need to be conquered. On one hand, the design of AI should be tailored to work settings in order to maximize its value generation and minimize potential conflicts and risks. Various design features of AI (i.e., algorithm logic, appearance, language, output style, content characteristics, affection expression, etc.) that involve the principles of transparency, understandability, fairness will induce different reactions and performance from human employees. Unexpected outcomes, whether good or bad, may also arise from the evolving AI with self-learning capabilities. On the other hand, human employees also need to adapt to the changes brought by AI to the work environment, realize their own value, and gain a sense of happiness, security, and fulfillment. If human employees do not gradually learn and adapt as they collaborate with AI, it will result in negative outcomes.
This track focuses on the related topics that address these two-fold challenges in the process of achieving Human-AI integration in organizations. We welcome research related to the important issues involved in this process, such as how various forms of AI (i.e., AI for work support or AI for management) influence (i.e., empowering or oppressing) human employees and reshape their work context, how human employees and AI evolve with each other, how to design and implement more appropriate and ethical AI, how the characteristics of the environments (i.e., types of industries) influence this process, etc.

Topics

1. AI-Human interactions in organizations
2. AI-Human collaboration in team
3. Individual or collective reliance on AI in organizations
4. AI-enabled Technostress in organizations
5. Algorithmic management and employees’ performance
6. Algorithmic management and employees’ wellbeing
7. Algorithmic management and power structures in organizations
8. Algorithmic management and colleagues’ relationships
9. AI related security behaviors in organizations
10. AI monitoring in organizations
11. Substitution and complementation between machine learning and human learning
12. Design of AI for AI-Human integration in organizations
13.Mutual abuse between human employees and AI
14. Ethics, standard and regulations of AI-Human integration in organizations