信息管理与商业智能系学术讲座

 

时   间:2024年2月26日 13:30-15:00

地   点:李达三楼104

主   题:Organizational Structures for Effective Coordination of Human Learning and Machine Learning: An Agent-Based Simulation Study

报告人:Ning Nan (南宁), Associate Professor, University of British Columbia

内容摘要:

To contribute to organizational learning performance, machine learning (ML) systems can be centrally integrated as a global intelligent system, or less centrally as team members or personal assistants. We develop an agent-based model to study how the different ways to integrate ML into organizational structure affect organizational learning performance. We find that more centrally integrated ML tends to produce greater levels of knowledge initially because the ML system can rapidly exploit a broader range of diverse perspectives. However, less centrally integrated ML enhances long-term organizational learning performance because it sustains the exploration of diverse human beliefs. Our study further shows that in an organization with a given way of ML integration, how humans learn and what influence humans exert on ML systems can affect the highest achievable learning performance. Finally, we find that problem complexity and environmental turbulence are important contingencies in harvesting benefits from ML systems. Our study updates the theoretical guidance for the use of structural design as a coordination mechanism to balance knowledge exploitation and exploration in organizational learning. Our model bridges the enduring research on organizational structure and the emerging scholarship on ML. It provides a virtual lab for us and future research to untangle the tradeoff between ML capability and human belief diversity in the AI age.

个人简介:

Ning Nan (南宁)is an Associate Professor of Management Information Systems at the Sauder School of Business at the University of British Columbia.  Her research applies the complex adaptive systems paradigm to examinations of the uses and impact of information and communication technology on business and society.  Her current research topics include the application of digital technologies to organizational learning, climate change, and smart cities. Ning Nan has published in MIS Quarterly, Journal of Management Information Systems, Journal of the Association for Information Systems, and IEEE Transactions on Software Engineering, among others.  She is an Associate Editor at Information Systems Research. She received her Ph.D. degree in Business Information Technology from the University of Michigan’s Ross School of Business. 

信息管理与商业智能系

2024-1-15