市场营销学系学术讲座

时间：2024年5月24日13:30-15:00

地点：思源楼 624

主题：A case study of adopting machine learning based framework for management research: Machine learning discovers that power distance is a predictor of trust in AI

主讲人：Abhishek Sheetal Research Assistant Professor

The Hong Kong Polytechnic University

主持人：余伊琦青年副研究员

摘要:

The development of AI/ML tools, societal perceptions of AI, criticisms of AI, and the use of AI as an analytical method are the four ways in which management researchers use machine learning methods in their work. As more and more researchers attempts to use AI as an analytical tool, this research area faces a reproducibility crisis because of the lack of a clear framework about how to use AI as an analytical tool. I propose Machine Learning Quantitative Grounded Theory (MLQGT) as a solution, which draws on the concept of abduction conceptualized by 19th-century physicist Charles Sanders Peirce. Using this framework, I demonstrate the application of machine learning methods to a topic that many social scientists are currently grappling with, trust in AI. China is the world leader in using AI technologies in everyday life. What cultural factors explain why trust in AI is so high in China but so low in other countries? This research shows that MLQGT can help provide answers, and oftentimes novel answers, to questions that are difficult to address otherwise.

简介:

Abhishek conducts research at the intersection of AI technologies and management science. As a computer systems architect prior to joining academia, Abhishek developed public goods computer technologies, such as the USB and the Ethernet. For Abhishek, computer technologies exist to make people’s lives better and to solve societal problems, and AI/ML technologies are no different. Using AI/ML as a mere computing machine to analyze data for novel research insights or for better policy making is a departure from other current mainstream research that are focused on how AI is perceived in society or how organizations are planning to adopt these new technologies. Offering insight into the real-world value of this perspective on AI/ML, his first research article was featured in The New York Times. Abhishek has a bachelor's degree in computer engineering, master’s degrees in computer engineering, economics, and business administration, and a PhD in Management.